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287 results for “Augmented Reality”
FIGURE 20. Snapcodes for A in Designing scientifically-grounded paleoart for augmented reality at La Brea Tar Pits
FIGURE 20. Snapcodes for A. saber-toothed cat, B. dire wolf, and C. Shasta ground sloth. Using the popular Snapchat app, these codes activate interactive AR experiences.
FIGURE 16 in Designing scientifically-grounded paleoart for augmented reality at La Brea Tar Pits
FIGURE 16. Low poly reconstruction of the extinct Harlan's ground sloth (Paramylodon harlani). To view this model in 3D, please see the online version of this article.
FIGURE 10 in Designing scientifically-grounded paleoart for augmented reality at La Brea Tar Pits
FIGURE 10. Low poly reconstruction of a generic extinct American lion (Panthera atrox). To view this model in 3D, please see the online version of this article.
FIGURE 1 in Designing scientifically-grounded paleoart for augmented reality at La Brea Tar Pits
FIGURE 1. The iconic Columbian mammoth family at La Brea Tar Pits sculpted by Howard Ball. Image by Y-Z on free- imageslive.co.uk.
Data study "The Impact of Augmented Reality on Biodiversity Learning in a Pedagogical Scenario Based on Analogical Reasoning: An Experimental Study"
<p>This data was collected in 2023 as part of a study on the impact of location-based AR on biodiversity education. </p>
BRAIN Journal-Participative Teaching with Mobile Devices and Social Networks for K-12 Children-Figure 4. Augmented Reality with video movie and social media (a vertical loom in front of two reconstructed kilns and a wall of a Roman villa rustica)
<p>The third stage was represented by the 3D virtual reconstruction process of the historical contexts, in our case a prehistoric village and a complete Roman villa rustica, with the help of students from the Design Department, NUA, coordinated by Professor Arch. Andreea Hasnaş. The AR application was created and tested on two commercial AR platforms, Layar and Junaio, and recently moved on the Aurasma platform (https://www.aurasma.com/). The POIs were augmented with the 3D virtual reconstructions, and also with 2D images and videos representing 3D virtual tours and technological processes (Figures 3, 4, 5). The AR application was connected to teachers’ emails and to Twitter, Facebook and Google+ project’s pages. </p>
BRAIN Journal-Participative Teaching with Mobile Devices and Social Networks for K-12 Children-Figure 3. Augmented Reality with archaeological stratigraphy (a prehistoric house and a Roman villa reconstructed in 3D)
<p>The third stage was represented by the 3D virtual reconstruction process of the historical contexts, in our case a prehistoric village and a complete Roman villa rustica, with the help of students from the Design Department, NUA, coordinated by Professor Arch. Andreea Hasnaş. The AR application was created and tested on two commercial AR platforms, Layar and Junaio, and recently moved on the Aurasma platform (https://www.aurasma.com/). The POIs were augmented with the 3D virtual reconstructions, and also with 2D images and videos representing 3D virtual tours and technological processes (Figures 3, 4, 5). The AR application was connected to teachers’ emails and to Twitter, Facebook and Google+ project’s pages. </p>
Collaborative Program Comprehension based on Augmented Reality (Evaluation Results of Master's Thesis)
<p>The dataset contains feedback generated through a survey for an augmented reality approach in the ExplorViz project.</p> <p>The dataset includes the results for a pilot study with two probands and the results for a case study with 20 probands.</p>
Exploring Augmented Reality Privacy Icons for Smart Home Devices and their Effect on Users' Privacy Awareness
<p><strong>Exploring Augmented Reality Privacy Icons for Smart Home Devices and their Effect on Users' Privacy Awareness</strong></p> <p><strong>Authors</strong></p> <p>Kathrin Knutzen, Florian Weidner, Wolfgang Broll</p> <p> </p> <p><strong>About</strong></p> <p>This data represents the supplementary material for the conference paper with above title submitted at ISMAR 2021.</p> <p> </p> <p><strong>Contents</strong></p> <p>The supplementary material contains five files:</p> <ol> <li>The abstraction of paraphrases and transcripts after each condition respectively.<br> According to qualitative content analysis procedure, the conducted interviews were transcribed, paraphrased and subsequently abstracted to generate a category system. Every category is described with a definition and some exemplary quotes. Statements of participants are condensed and abstracted. Number of participants who made statements regarding a category, and most prominent valence are taken as basis to generate tree maps in Figure 5 and 6.<br> Please note that the prevalences represent the views or opinions of the participants on the single categories. Also, the mentioned categories have several subcategories and only the most important regarding privacy awareness are mentioned in the article.<br> <br> Transcripts, audio files and paraphrases are available upon request.</li> <li>The experimental task description. It served as exposition for the task that the participants had to complete.</li> <li>The interview guideline. Please note that this study was part of a larger project that also focused on topics such as usability and immersion, however, the article reports only on privacy awareness.</li> <li>The R script file to generate the tree maps in Figures 5 and 6. The dataset is created using data from the abstraction Excel sheet.</li> <li>A demonstration video of the experimental setup.</li> </ol>
Comparing 2D and Augmented Reality Visualizations for Microservice System Understandability: Protocol And Dataset
<p>Comparing 2D and Augmented Reality Visualizations for Microservice System Understandability: Dataset.</p> <p>This dataset includes:</p> <ol> <li>The tools executable files and JSON representations.</li> <li>The tools screenshots.</li> <li>The participants classification data.</li> <li>Questionnaire Form.</li> <li>Training Materials.</li> <li>Testing Tasks.</li> </ol> <p> </p> <p><strong>Our Paper is at ICPC conference with title</strong>: Comparing 2D and Augmented Reality Visualizations for Microservice System Understandability: A Controlled Experiment</p>
Dataset for the assessment of presence and performance in an augmented reality environment for motor imitation learning: a case-study on violinists.
<p><strong>Data description</strong></p> <ol> <li>Repository structure</li> </ol> <p>The repository contains several zip files, which contain a set of individual data files. We describe the general content of every zip file and supplement this information with a table describing the individual data files in the zip file. An overview of the different zip-files is given in Table 1.</p> <p> </p> <table> <tbody> <tr> <td> <p>Zip-files in repository</p> </td> <td> <p>description</p> </td> </tr> <tr> <td> <p>Labeled_MoCap_Data.zip</p> </td> <td> <p>Labeled motion capture data</p> </td> </tr> <tr> <td> <p>Joint_Angle_Data.zip</p> </td> <td> <p>Joint angles extracted from mocap data</p> </td> </tr> <tr> <td> <p>Analyzed_Data.zip</p> </td> <td> <p>Filtered and analyzed mocap data</p> </td> </tr> <tr> <td> <p>Audio_Data.zip</p> </td> <td> <p>Audio data participants</p> </td> </tr> <tr> <td> <p>Questionnaire_Data.zip</p> </td> <td> <p>Questionnaire data</p> </td> </tr> <tr> <td> <p>Scores.zip</p> </td> <td> <p>Scores played by participants</p> </td> </tr> <tr> <td> <p>Avatar_Data.zip</p> </td> <td> <p>All data collected for the avatars</p> </td> </tr> </tbody> </table> <p> Table 1: overview of different zip-files in repository.</p> <p> </p> <ol> <li> </li> </ol> <p>Csv format with labeled MoCap Data, including data labels. Every column is a data stream from a marker. Every marker has 3 data streams, referring to the x, y, and z coordinates of the marker position. In addition, the violin (3-4 markers) and the violin bow (3 markers) are labelled as well. An overview of the different labels and their meaning is given in Table 2. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (MoCap), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_MoCap.csv’ for a participant (see Table 2).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Labeled_MoCap_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Labeled MoCap Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 2: content and file structure of Labeled_MoCap_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>Csv format with joint angles, including data labels. Every column is a data stream from a joint. Every joint has a varying number of data streams, depending on the calculated angles. In addition to joint angles, the angles of the instrument relative to the body are given as well, the distances of the bow to the bridge, and to distances of the bow to the strings, respectively. An overview of the different labels and their meaning is given in Table 3. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (JointAngles), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_JointAngles.csv’ for a participant (see Table 3).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Joint_Angle_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Joint Angle Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 3: content and file structure of Joint_Angle_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>Time series of filtered and analyzed data. The distances of the bow to the bridge and frog, are filtered so that only bow strokes with a certain bowing length and a certain loudness level are retained. The resulting collection of regions-of-interest (ROIs) is then analyzed for movement smoothness (as assessed with the SPARC index), and a comparison is made between the profile of avatar bowing movements and participant bowing movements by means of the Procrustes distance. These data are presented as csv files with 4 columns: SPARC index per ROI, Procrustes distance between the bow movement of the avatar and participant, index of start and end of each ROI. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (AnalyzedData), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_ AnalyzedData.csv’ for a participant (see Table 4).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Analyzed_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Analyzed Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 4: content and file structure of Analyzed_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>Wav-files are presented per participant (P001-P011), per trial (T1-T4), per condition (2D/3D). Audio files contain 2 tracks (left and right microphone), i.e., they are stereo recordings. Additionally, the data type (Audio), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_Audio.wav’ for a participant (see Table 5).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Audio_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Audio Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 5: content and file structure of Audio_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>The results of 5 standardized questionnaires are presented: the Makransky Multimodal Presence Questionnaire (the social presence subset or MPQS and the physical presence subset or MPQP), the Witmer Presence Questionnaire (WPQ), the Immersive Tendencies Questionnaire (ITQ), the Musical Sophistication Index (MSI), and the Sense of Musical Agency Questionnaire (SOMA). Additionally, demographic data (DQ) were collected, along with some open questions (OQ). The answers to the questionnaires are organized in 3 csv files: ‘MB.csv’, containing answers to the questionnaires presented before the first session (ITQ, MSI and some DQ); and ‘C1.csv’ and ‘C2.csv’, containing the answers to the questionnaires presented before and after each session (MPQS, MPQP, WPQ, SOMA, some DQ and some OQ) in the first and second condition, respectively. A csv file named ‘Legend.csv’ indicates the codes of all the questions, and where the answers to the questions can be found (see Table 6). Since some participants answered in Dutch, all responses were translated to English before adding them to the repository.</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Questionnaire_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> </tr> <tr> <td> <p>C1.csv</p> </td> <td> <p>questionnaires and answeres of condition 1</p> </td> </tr> <tr> <td> <p>C2.csv</p> </td> <td> <p>questionnaires and answeres of condition 2</p> </td> </tr> <tr> <td> <p>MB.csv</p> </td> <td> <p>questionnaires and answers related to musical background</p> </td> </tr> <tr> <td> <p>Legend.csv</p> </td> <td> <p>questions and question codes</p> </td> </tr> </tbody> </table> <p>Table 6: content and file structure of Questionnaire_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>The scores which were played by both the avatar and the participants are provided, with the correct bowings and articulations. The fragment and the violin section are indicated in the filename. E.g., ‘First_Violin_F2.pdf’, contains the scores of fragment F2, as played by the first violins. See Table 7 for an overview of the file structure and the content.</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Scores.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> </tr> <tr> <td> <p>First_Violin_F1.pdf</p> </td> <td> <p>Fragment F1 as played by the first violin section</p> </td> </tr> <tr> <td> <p>First_Violin_F2.pdf</p> </td> <td> <p>Fragment F2 as played by the first violin section</p> </td> </tr> <tr> <td> <p>Second_Violin_F3.pdf</p> </td> <td> <p>Fragment F3 as played by the second violin section</p> </td> </tr> <tr> <td> <p>Second_Violin_F4.pdf</p> </td> <td> <p>Fragment F4 as played by the second violin section</p> </td> </tr> </tbody> </table> <p>Table 7: content and file structure of Scores.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>This directory contains files in csv format with labeled MoCap Data, including data labels. Every column is a data stream from a marker. Every marker has 3 data streams, referring to the x, y, and z coordinates of the marker position. In addition, the violin (3-4 markers) and the violin bow (3 markers) are labelled as well. One data file per avatar (First Violin or Second Violin) is presented. Additionally, the data type (MoCap), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘First_Violin_F2_MoCap.csv’ for an avatar (see Table 8).</p> <p>Additionally, the directory contains files in csv format with joint angles, including data labels. Every column is a data stream from a joint. Every joint has a varying number of data streams, depending on the calculated angles. In addition to joint angles, the angles of the instrument relative to the body are given as well, the distances of the bow to the bridge, and the distances of the bow to the strings, respectively. One data file per avatar (First Violin or Second Violin) is presented. Additionally, the data type (JointAngles), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘Second_Violin_F3_JointAngles.csv’ for an avatar (see Table 8).</p> <p>Finally, this directory contains wav-files per avatar (First Violin or Second Violin). Audio files contain 2 tracks (left and right microphone), i.e., they are stereo recordings. Additionally, the data type (Audio), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘First_Violin_F1_Audio.wav’ for an avatar (see Table 8).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Avatar_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> </tr> <tr> <td> <p>First_Violin_F1_MoCap.csv</p> </td> <td> <p>MoCap data of the first violin avatar, playing fragment F1</p> </td> </tr> <tr> <td> <p>First_Violin_F1_JointAngles.csv</p> </td> <td> <p>Joint angle data of the first violin avatar, playing fragment F1</p> </td> </tr> <tr> <td> <p>First_Violin_F1_Audio.wav</p> </td> <td> <p>Audio data of the first violin avatar, playing fragment F1</p> </td> </tr> <tr> <td> <p>First_Violin_F2_MoCap.csv</p> </td> <td> <p>MoCap data of the first violin avatar, playing fragment F2</p> </td> </tr> <tr> <td> <p>First_Violin_F2_JointAngles.csv</p> </td> <td> <p>Joint angle data of the first violin avatar, playing fragment F2</p> </td> </tr> <tr> <td> <p>First_Violin_F2_Audio.wav</p> </td> <td> <p>Audio data of the first violin avatar, playing fragment F2</p> </td> </tr> <tr> <td> <p>Second_Violin_F3_MoCap.csv</p> </td> <td> <p>MoCap data of the second violin avatar, playing fragment F3</p> </td> </tr> <tr> <td> <p>Second_Violin_F3_JointAngles.csv</p> </td> <td> <p>Joint angle data of the second violin avatar, playing fragment F3</p> </td> </tr> <tr> <td> <p>Second_Violin_F3_Audio.wav</p> </td> <td> <p>Audio data of the second violin avatar, playing fragment F3</p> </td> </tr> <tr> <td> <p>Second_Violin_F4_MoCap.csv</p> </td> <td> <p>MoCap data of the second violin avatar, playing fragment F4</p> </td> </tr> <tr> <td> <p>Second_Violin_F4_JointAngles.csv</p> </td> <td> <p>Joint angle data of the second violin avatar, playing fragment F4</p> </td> </tr> <tr> <td> <p>Second_Violin_F4_Audio.wav</p> </td> <td> <p>Audio data of the second violin avatar, playing fragment F4</p> </td> </tr> </tbody> </table> <p>Table 8: content and file structure of Avatar_Data.zip.</p> <p> </p>
PoqueiraAR: Dataset and Metrics from Augmented Reality App in Barranco del Poqueira in the Alpujarra Granadina
<p>This dataset is related to an Augmented Reality application implemented in the Sierra Nevada National Park, specifically in the Barranco del Poqueira. This application has been designed to enhance the experience of visitors walking a circular path that connects the three villages of the ravine: Pampaneira, Bubión and Capileira, offering seven points of interest.</p><p>The dataset covers the period from June 2022 to October 2023 and includes information on the number of downloads, download dates, types of devices used to download the application, geographic origin of the devices, attractions visited and most demanded audiovisual resources.</p><p>These data provide an objective view of the effectiveness of the application in improving the visitor experience and its impact on the tourism promotion of Barranco del Poqueira. In addition, they provide relevant information about user preferences, which can guide future updates and improvements in the Augmented Reality application. The application contributes to enrich the visit to these villages and provides useful data for the sustainable management of tourism in this region of Sierra Nevada.</p>
Spacial Augmented Reality
<p>Spatial Augmented Reality (SAR) is the little known half-sibling of Augmented Reality (AR). While AR is well known to most of us, thanks to the ubiquity of the multifunctional smartphones in our pockets, SAR has been used mainly in the confined spaces of computer research labs and high-budget entertainment events. Only recently, thanks to developments in hard- and software, the tools – such as tracking based projection mapping – are now ready to be used in a broader context.</p>
Sonic Sculptural Staircase experience in Head-Mounted Augmented Reality
<p>This is the demo video of my work Sonic Sculptural Staircase used for the submission in NIME.</p>
Evaluating Augmented Reality Light Probe Estimation Techniques using a Single Camera (Supplemental Material)
<p>This repository contains the dataset for the paper "Evaluating Single Camera Augmented Reality Light Probe Estimation Techniques".</p> <p>The data archive includes:</p> <ul> <li>The complete image set (3 scenes with 6 techniques and ground truth in 90 time points)</li> <li>SSIM data of the panoramas as a CSV file</li> <li>SSIM data of the rendered images as a CSV file</li> <li>Various graphs to visualize the data</li> <li>R files used to plot the graphs</li> </ul> <p>The data archive includes additional plots that are not included in the paper.</p>
Bridge Cracks Monitoring: Detection, Measurement, and Comparison using Augmented Reality
<p>Crack occurrence and propagation are among critical factors that affect the performance and lifespan of civil infrastructures such as bridges. Consequently, numerous crack detection and measurement methods have been proposed and developed in the recent decades in the areas of Structural Health Monitoring and non-destructive testing. Many novel technologies have emerged with the potential to overcome the limitations of the presented techniques of crack detection and characterization. Crack detection and characterization method used in this research lies in supplementing human visual inspection capabilities in a systematic manner through an appropriate level of automation. The Augmented Reality (AR) tool developed in this project allows a user to perform tasks in a real-world environment while visually receiving supplementary 3D computer-generated information to support the tasks. More specifically, we developed a crack detection/characterization tool in this research and deployed it in Microsoft HoloLens smart glasses. This AR tool provides the user with automatic data collection capability through AR headset camera and is a means of hands-free data sharing for inspectors while conducting their normal inspection. We conducted several laboratory and field experiments by which we evaluated the effectiveness of the developed crack detection and measurement system. The result confirm that the AR tool devised in this project has the potential to help the inspection process in terms of time, comfort and accuracy.</p>
LFW-Beautified: A Dataset of Face Images with Beautification and Augmented Reality Filters
<p><strong>LFW-Beautified: A Dataset of Face Images with Beautification and Augmented Reality Filters</strong></p> <p><strong>Usage</strong></p> <ul> <li>Download the compressed files (13 in total) and uncompress them</li> <li><strong>Please cite reference 1) below in your publications if you make use of the data of this repository</strong></li> </ul> <p><strong>People & Contact</strong></p> <ul> <li><a href="http://wiki.hh.se/caisr/index.php/Fernando_Alonso-Fernandez">Fernando Alonso-Fernandez</a> (contact person).</li> </ul> <p><strong>References</strong></p> <ol> <li>Hedman, P., Skepetzis, V., Hernandez-Diaz, K., Bigun, J., Alonso-Fernandez, F., "On the Effect of Selfie Beautification Filters on Face Detection and Recognition" <a href="https://github.com/HalmstadUniversityBiometrics/LFW-Beautified/blob/main">https://arxiv.org/abs/2110.08934</a></li> <li>Hedman, P., Skepetzis, V., The Effect of Beautification Filters on Image Recognition: "Are filtered social media images viable Open Source Intelligence?" Master Thesis at Halmstad University, Sweden (Master’s Programme in Network Forensics) <a href="http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44799">http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44799</a></li> </ol> <p> </p>
Augmented Reality Soundscapes - mit maschinellem Lernen Klangkulissen von zukünftigen Bauvorhaben generieren
<p><b>Abstract</b></p><p class="dhik-abstract-content">Das vorgestellte Projekt zeigt auf, wie praxisorientiert und interdisziplinär das Potenzial von generierten Klangkulissen mittels maschinellen Lernens und Audio Augmented Reality in der Raumplanung untersucht wurde.</p><p></p><p><b>Weitere Beiträge aus dem DHIK-Forum 2022 auf Zenodo:</b></p><p class="dhik-session-list"></p><ul><li>Session #1: Viktor Sigrist: Internationalisierung - Partnerschaften für den Ausbau von Forschung und Entwicklung (DOI:<a href="https://zenodo.org/record/7123701">10.5281/zenodo.7123701</a>)</li><li>Session #2: Dieter Leonhard: DHIK- Strategien der internationalen Zusammenarbeit in Forschung und Lehre (DOI:<a href="https://zenodo.org/record/7123456">10.5281/zenodo.7123456</a>)</li><li>Session #3: Stephen Wittkopf: Wissens- und Innovationstransfer - Interdisziplinäre Zusammenarbeit mit Unternehmen und Institutionen (DOI:<a href="https://zenodo.org/record/7025707">10.5281/zenodo.7025707</a>)</li><li>Session #4: Xiao Feng: CDHAW - Chinesisch-Deutsche Hochschule für Angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123458">10.5281/zenodo.7123458</a>)</li><li>Session #5: Antonio Pita und Isabel Kreiner: Academy-Industry-Collaboration - Outreach Strategy (DOI:<a href="https://zenodo.org/record/7123460">10.5281/zenodo.7123460</a>)</li><li>Session #6: Martin Sternberg: Promotionsrecht – aktueller Stand an deutschen Hochschulen für angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123757">10.5281/zenodo.7123757</a>)</li><li>Session #7: Adrian Derungs: Duo mit Innovationskraft - Zusammenspiel von Forschung und Wirtschaft in der Zentralschweiz (DOI:<a href="https://zenodo.org/record/7123767">10.5281/zenodo.7123767</a>)</li><li>Session #8: Theres Paulsen: Transdisziplinäre Forschung - komplexe gesellschaftliche Herausforderungen erfordern diverse Ansätze (DOI:<a href="https://zenodo.org/record/7123769">10.5281/zenodo.7123769</a>)</li><li>Session #9: Jörg Schneider: International research collaboration - New funding opportunities for universities of applied sciences (DOI:<a href="https://zenodo.org/record/7123771">10.5281/zenodo.7123771</a>)</li><li>Session #10: Cornelia Spycher und Matthew Whellens: Horizon Europe - overview of funding opportunities for your research and innovation (DOI:<a href="https://zenodo.org/record/7123773">10.5281/zenodo.7123773</a>)</li><li>Session #11: Janique Siffert: Eureka Eurostars - erfolgreiche Förderung für internationale Innovationsprojekte (DOI:<a href="https://zenodo.org/record/7123777">10.5281/zenodo.7123777</a>)</li><li>Session #12: Ludger Fischer: Energy Lab - ein Netzwerk für innovative Lösungen im Energiebereich (DOI:<a href="https://zenodo.org/record/7123779">10.5281/zenodo.7123779</a>)</li><li>Session #13: Jörg Worlitschek: Thermal energy storage - heating the north, cooling the south (DOI:<a href="https://zenodo.org/record/7123781">10.5281/zenodo.7123781</a>)</li><li>Session #14: Jonas Mühlethaler: Neues DC Microgrid-Konzept – netzunabhängige Elektrifizierung in Entwicklungsländern (DOI:<a href="https://zenodo.org/record/7123783">10.5281/zenodo.7123783</a>)</li><li>Session #15: Tommy Claussen: Dekarbonisierung des Gebäudesektors - digitale Transformation in der Gebäudetechnik und im Gebäudemanagement (DOI:<a href="https://zenodo.org/record/7123785">10.5281/zenodo.7123785</a>)</li><li>Session #16: Christoph Imboden: Flexibility solutions - making the power grid fit for the future (DOI:<a href="https://zenodo.org/record/7123787">10.5281/zenodo.7123787</a>)</li><li>Session #17: Uwe Schulz: Spielerisches Sarnetz - Simulationen für die fossile Unabhängigkeit einer Ortschaft (DOI:<a href="https://zenodo.org/record/7123790">10.5281/zenodo.7123790</a>)</li><li>Session #18: Jana Koehler: Künstliche Intelligenz – Erfolg durch Erwünschtheit, Machbarkeit und Wirtschaftlichkeit (DOI:<a href="https://zenodo.org/record/7123792">10.5281/zenodo.7123792</a>)</li><li>Session #19: Rolf Kamps: KI in der Prävention - Befragungsmethoden und Schulungen trainieren, Krankheitserreger erkennen (DOI:<a href="https://zenodo.org/record/7123794">10.5281/zenodo.7123794</a>)</li><li>Session #20: Gwendolyne Pascua: Artificial Intelligence in Space - CIMON assisting astronauts on the International Space Station (DOI:<a href="https://zenodo.org/record/7123796">10.5281/zenodo.7123796</a>)</li><li><b>Session #21: Tobias Matter et.al.: Augmented Reality Soundscapes - mit maschinellem Lernen Klangkulissen von zukünftigen Bauvorhaben generieren (<a href="#collapseTwo">Video</a>)</b></li><li>Session #22: Angela Nicoara: Internet of Things - transforming businesses, people's lives and driving growth in the coming years (DOI:<a href="https://zenodo.org/record/7123800">10.5281/zenodo.7123800</a>)</li><li>Session #23: Adrian Koller: Feldrobotik - unermüdliche und zunehmend intelligentere Hilfe in der Landwirtschaft (DOI:<a href="https://zenodo.org/record/7123802">10.5281/zenodo.7123802</a>)</li><li>Session #24: Widar von Arx et.al.: Realisierung der Verkehrswende - Einfluss der Preispolitik in der Mobilität (DOI:<a href="https://zenodo.org/record/7124000">10.5281/zenodo.7124000</a>)</li><li>Session #25: Andreas Liebrich: Tourismusdateninfrastruktur - Was die Schweiz von Europa lernen kann (DOI:<a href="https://zenodo.org/record/7123806">10.5281/zenodo.7123806</a>)</li><li>Session #26: Frank Pöhlau und Stefan May: Find life on Mars - Schülerprojekte zur mobilien Robotik (DOI:<a href="https://zenodo.org/record/7123808">10.5281/zenodo.7123808</a>)</li><li>Session #27: Jiayun Shen: Open Innovation - Innovationsmanagement bei der Schweizerischen Post (DOI:<a href="https://zenodo.org/record/7123810">10.5281/zenodo.7123810</a>)</li><li>Session #28: Tobias Specker: Interkulturelles Management – innovative Konzepte zum Ausbau der China-Kompetenzen an Hochschulen (DOI:<a href="https://zenodo.org/record/7123812">10.5281/zenodo.7123812</a>)</li><li>Session #29: Elena Algorri: Swimming robots - exploring the unterwater from the surface (DOI:<a href="https://zenodo.org/record/7123814">10.5281/zenodo.7123814</a>)</li><li>Session #30: Sergio Camacho: Robotics and Digital Systems Engineering at the Tec de Monterrey (DOI:<a href="https://zenodo.org/record/7123816">10.5281/zenodo.7123816</a>)</li><li>Session #31: Thomas Dorn: Industrie 4.0 - Forschungskooperationen mit der CDHAW und der Tongji Universität Shanghai (DOI:<a href="https://zenodo.org/record/7123818">10.5281/zenodo.7123818</a>)</li><li>Session #32: Walter Reichert et.al.: Kollaboration und Unterstützung - Mobile Robotik und Exoskelette in der flexiblen Produktion (DOI:<a href="https://zenodo.org/record/7123820">10.5281/zenodo.7123820</a>)</li><li>Session #33: Louis Palmer: Solar Butterfly - climate pioneer world tour supported by HSLU (DOI:<a href="https://zenodo.org/record/7123822">10.5281/zenodo.7123822</a>)</li></ul><p></p>
Augmented reality uses cases
<p>Augmented reality is technology that combines virtual reality with the real world. This video discuss the three categories of augmented reality uses.</p>
Automated Usability Evaluation of Augmented Reality Applications
<p>Research data for my master thesis on the topic: "Automated Usability Evaluation of Augmented<br> Reality Applications"</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.