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55 results for “Video Animation”
Data and Videos for Argos: a toolkit for tracking multiple animals in complex visual environments
<p>Original videos used and data generated for the article "Argos: a toolkit for tracking multiple animals in complex visual environments".</p> <p>The data contains original videos used as input to the Argos Tracking tool, the generated raw tracks in Pandas-HDF5 format, and the corrected tracks after processing with Argos Review tool.</p> <p>It also includes a zip archive with ground truth tracks along with tracks detected from two videos by Argos and several other tracking tools for comparison using the HOTA metric organized in a folder structure suitable for the TrackEval tool.</p>
Animation video on responsible research and innovation (RRI)
<p>This is a short animation video about responsible research and innovation. Watch it here: https://youtu.be/fOG5U2QweBo</p> <p>In research guided by responsible research and innovation (RRI), members of society work with scientists to align both the entire research process and its results with societal needs. The researcher and the research institute or research funder turn openly to citizens and involve the relevant societal actors in formulating research questions and collecting and analysing data. In RRI-guided research, scientists never forget to ask themselves: will our research do good to society and the Earth? What will its long-term social, ethical, and ecological consequences be? If a researcher or research-performing organisation integrates responsibility into their work, they will feel more useful and impactful in their profession, all in order to improve the lives of their fellow human and non-human beings. For this reason, it is important for researchers to reflect on their own organisational operations and change their daily routines. This is exactly what the Co-Change Project started to experiment with. In order to raise awareness of RRI, the project initiated ongoing deliberation within and beyond its own organisations through discussing ethics, gender, and open-science-related topics that engage all units that deal with research and innovation, as well as involving external experts and stakeholders in co-creating change.</p> <p> </p>
ROADMAP Animation Video
<p>This animation movie of ROADMAP describes the importance of antimicrobial resistance, how ROADMAP supports prudent use of antimicrobials in livestock sector and ROADMAP's tailored solutions in case studies and living labs in 10 different countries in pig, poultry, dairy and veal production farms.</p> <p> </p> <p>French version: https://www.youtube.com/watch?v=YP-02Io4SoU&t=57s</p> <p>Spanish version: https://www.youtube.com/watch?v=vlew_jIYuOs&t=13s</p> <p>Italian version: https://www.youtube.com/watch?v=qi_00E9Yqmc&t=6s</p> <p> </p> <p>Learn more about ROADMAP by visiting the website: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbXBNN3NtZFlfa3dQYWpmem9aSE1vNzA2OHdWd3xBQ3Jtc0ttZUExc2xDU28yaVVacjVSTFZia1lWbVAzNUJmVDdDbElpdkg5UTNrei15VTUzbjZocU9QbDFYaFlRRTRFcWVPOWEweUZ3dG5saTZuVDNLLWR5ODVTcmRzMU90R1NtVmJsTVdoakVMSHMtUkZSZnY5UQ&q=https%3A%2F%2Fwww.roadmap-h2020.eu%2F&v=7FvY1wzbjhg">https://www.roadmap-h2020.eu/</a></p>
paperChain - Video Animation - Circular Case 4 (Sweden)
<p>This animation video summarises in approximately two minutes the most relevant results of the implementation of paperChain's Circular Case.</p>
paperChain - Video Animation - Circular Case 3 (Slovenia)
<p>This animation video summarises in approximately two minutes the most relevant results of the implementation of paperChain's Circular Case.</p>
paperChain - Video Animation - Circular Case 1 (Portugal)
<p>This animation video summarises in approximately two minutes the most relevant results of the implementation of paperChain's Circular Case.</p>
paperChain - Video Animation - Circular Case 1 (Portugal) - Portuguese version
<p>This animation video summarises in approximately two minutes the most relevant results of the implementation of paperChain's Circular Case.</p>
Animal Re-Identification from Video
<p>Repository of annotated videos, images and extracted features of multiple animals</p> <p> </p> <p><strong>1. Videos</strong></p> <p>The videos are available in the file "videos.zip".</p> <p>The original videos included in this repository have been sourced from <a href="https://pixabay.com/">Pixabay</a> under Pixabay License</p> <ul> <li>Free for commercial use</li> <li>No attribution required</li> </ul> <p>The video data is summarised below:</p> <table> <thead> <tr> <th><em>Short Name</em></th> <th><em>Video Name</em></th> <th><em># Frames</em></th> <th><em>Size</em></th> <th><em># Bounding boxes</em></th> <th><em># Identities</em></th> </tr> </thead> <tbody> <tr> <td>Pigs</td> <td>Pigs_49651_960_540_500f.mp4</td> <td>500</td> <td>( 960, 540)</td> <td>6184</td> <td>26</td> </tr> <tr> <td>Koi fish</td> <td>Koi_5652_952_540.mp4</td> <td>536</td> <td>( 952, 540)</td> <td>1635</td> <td>9</td> </tr> <tr> <td>Pigeons (curb)</td> <td>Pigeons_8234_1280_720.mp4</td> <td>443</td> <td>(1280, 720)</td> <td>4700</td> <td>16</td> </tr> <tr> <td>Pigeons (ground)</td> <td>Pigeons_4927_960_540_600f.mp4</td> <td>600</td> <td>( 960, 540)</td> <td>3079</td> <td>17</td> </tr> <tr> <td>Pigeons (square)</td> <td>Pigeons_29033_960_540_300f.mp4</td> <td>300</td> <td>( 960, 540)</td> <td>4892</td> <td>28</td> </tr> </tbody> </table> <p> </p> <p><strong>2. Annotated videos</strong></p> <p>The annotated videos are available in the file "annotated_videos.zip":</p> <ul> <li>Annotated_Pigs_49651_960_540_500f.mp4. Annotation contributed by <a href="https://github.com/LucyKuncheva/Animal-Identification-from-Video/blob/main/mas00a@bangor.ac.uk">Lucy Kuncheva</a></li> <li>Annotated_Koi_5652_952_540.mp4. Annotation contributed by <a href="https://github.com/LucyKuncheva/Animal-Identification-from-Video/blob/main/mas00a@bangor.ac.uk">Lucy Kuncheva</a></li> <li>Annotated_Pigeons_8234_1270_720.mp4. Annotation contributed by <a href="https://github.com/LucyKuncheva/Animal-Identification-from-Video/blob/main/wll19pkk@bangor.ac.uk">Wilf Langdon</a></li> <li>Annotated_Pigeons_4927_960_540_600f.mp4. Annotation contributed by <a href="https://github.com/LucyKuncheva/Animal-Identification-from-Video/blob/main/eeub05@bangor.ac.uk">Frank Krzyzowski</a></li> <li>Annotated_Pigeons_29033_960_540_300f.mp4. Annotation contributed by <a href="https://github.com/LucyKuncheva/Animal-Identification-from-Video/blob/main/wnw19njx@bangor.ac.uk">Owen West</a></li> </ul> <p> </p> <p><strong>3. Images</strong></p> <p>The individual images are in the file "images.zip".</p> <p>For each video, all the images are in the corresponding folder. Inside, there is a folder for each individual with all the images. The filename of each image includes the frame number.</p> <p> </p> <p><strong>4. Frames information</strong></p> <p>The correspondence between images and frames in the videos are in the file "frames.zip"</p> <p>The prefixes "h1_" and "h2_" denote, respectively, the first and second halves of the videos.</p> <p>The columns on these files are:</p> <ul> <li>x, y: coordinates in pixels of the top left corner of the bounding box.</li> <li>width, height: of the bounding box in pixels.</li> <li>frame: frame number.</li> <li>max_w, max_h.</li> <li>label: the label (class) number.</li> <li>image: file name.</li> </ul> <p> </p> <p><strong>5. Extracted features</strong></p> <p>Files with the extracted features are in "features.zip".</p> <p>The prefixes "h1_" and "h2_" denote, respectively, the data corresponding to the first and second halves of the videos.</p> <p>Five representations are used:</p> <ul> <li>"RGB" moments.</li> <li>"HOG": Histogram of Oriented Gradients</li> <li>"LBP": Local Binary Patterns.</li> <li>"AE": AutoEncoders.</li> <li>"MN2": extracted from a Keras MobileNetV2 model pre-trained on Imagenet</li> </ul> <p>The representation appears as a postfix in the file names.</p> <p>In each csv file, each image appears as a row. The feature values followed by the label (class) number.</p> <p> </p> <p><strong>6. Source code</strong></p> <p>Sample code (matlab & python) is available at <a href="https://github.com/admirable-ubu/animal-recognition">https://github.com/admirable-ubu/animal-recognition</a></p> <p> </p>
Ressources - Video games as a tool for ecological learning : the case of Animal Crossing - COROLLER & FLINOIS - 2023
<p>The present repository includes : </p> <ol> <li>Survey answers - 200 people, anonymized. Quizz about animals and vegetals that are and are not present in the game ANIMAL CROSSING NEW HORIZONS. Personal questions (age,, gender, location). Self assesment of "Naturalistic Fiber". At the end, question about the video game Animal CROSSING, and then free space</li> <li>Translated R code, based on the present dataset. Runs figures and tests used in our paper "Video games as a tool for ecological learning : the case of "Animal Crossing : New Horizons" during Covid-19 quarantine"</li> <li>The survey itself is available (in french unfortunately) at the following link : <a href="https://forms.gle/GgwULMcg8KnBqDt26">https://forms.gle/GgwULMcg8KnBqDt26</a>,<br> if the link is broken, please don't hesitate to contact me</li> <li>Nintendo Game Content guide at the following link : <a href="https://www.nintendo.co.jp/networkservice_guideline/en/index.html">https://www.nintendo.co.jp/networkservice_guideline/en/index.html</a></li> <li>Appendix (S1 : table of raw datas ; S2 : Normal and QQ plots)</li> <li>Approval of Ethical Research Committee of Université de Sherbrooke (Canada, QC)<br> </li> </ol> <blockquote> <p><em>" [...] furthermore, after reviewing the application for review, no ethical issues were identified by the committee.The committee notes that:The data were collected from a population of individuals who do not a priori present the characteristics of a vulnerable population; The risks associated with participation in the research are minimal; The data collected are anonymous; Individuals have been informed that the data may be used for scientific purposes; However, we remind you that in the future, any research project, as defined in the policy, must be approved by the research ethics committee before proceeding with the collection of data. Therefore, please accept this letter in lieu of an ethics certificate from the </em><em>Research Ethics Board - Education and Social Sciences of the Université de Sherbrooke. This letter may be used when submitting for publication or presentation of the results of this study or for any results of this study or for any other request related to the ethical approval of this project. "</em></p> <p><em>Mme Ariane Tessier<br> Coordonnatrice à l'éthique de la recherche - Université de Sherbrooke, CA QC</em></p> </blockquote> <p>If you have any problem with the present ressources, or if you want to work and publish works containing these datas, please contact me at : <br> simoncoroller.biologie@gmail.com CC : Simon.Coroller@usherbrooke.ca</p> <p>I would gladly discuss with you ! </p> <p>Best wishes.<br> <br> COROLLER & FLINOIS</p> <p> </p>
AI4DI Animated Project Introduction Video
<p>This animated video depicts the ECSEL JU project's AI4DI and how it addresses the needs of 5 diverse industrial sectors: Industrial Machinery, Automotive, Semiconductor, Food and Beverage, and Transportation</p>
Animated video presenting the advancements from AI4DI Supply Chain for Food and Beverage industries
<p>This animated video presents the dvancements from AI4DI Supply Chain for Food and Beverage industries.</p>
Data associated with: Recording animal-view videos of the natural world using a novel camera system and software package
<p>Data associated with Vasas V, Lowell MC*, Villa J*, Jamison QD*, Siegle AG*, Katta PVR*, Bhagavathula P*, Kevan PG, Fulton D, Losin N, Kepplinger D, Salehian S, Forkner RE, Hanley D (2023) Recording animal-view videos of the natural world using a novel camera system and software package. PLoS Biology. DOI: 10.1371/journal.pbio.3002444</p>
Internet_Animal_Video_Dataset
<p>Anonymized dataset repository for our study entitled "Millions of pet videos deepen our understanding of human-cat interactions with implications for management." All the .csv files are encoded with UTF-8.</p> <p> </p> <p>CommentData_{category}.csv includes: </p> <p>Video_pub_time: Publishing time of the video;</p> <p>Video_id: The unique ID assigned to the video;</p> <p>Video_tag: The tags of the video;</p> <p>Video_play: The Play count of the video;</p> <p>Video_favor: The Favor count (another popularity metric) of the video;</p> <p>Video_duration: The duration of the video;</p> <p>Comment_text: The raw comment texts;</p> <p>Comment_emoji: The emoji used in the comment;</p> <p>Comment_like: The count of likes the comment received;</p> <p>Comment_gender: The self-selected gender of the commenter. </p> <p> </p> <p>VideoTagData_category.csv includes:</p> <p>Video_pub_time: Publishing time of the video;</p> <p>Video_id: The unique ID assigned to the video;</p> <p>Video_tag: The tags of the video;</p> <p>Video_play: The Play count of the video;</p> <p>Video_favor: The Favor count (another popularity metric) of the video;</p> <p>Video_duration: The duration of the video;</p> <p> </p>
SUSHEAT Project Animation Video
<p>The Project Animation Video has been developed to support the dissemination and communication activities of the SUSHEAT project.</p> <p>This project is funded by the European Union under Grant Agreement 101103552. The views and opinions expressed are solely those of the author(s) and do not necessarily reflect the views of the European Union or the European Climate, Infrastructure and Environment Executive Agency (CINEA). Neither the European Union nor the granting authority can be held responsible for any use that may be made of the information it contains.</p>
SiC nano for PicoGeo project animated video
<p>This animated video is designed to reach the general public, given its cartoon form and its non-technical content that aims to present the project in general. However, it is also aimed at getting potential stakeholders attracted by the ideas conveyed by the project to take a more conscious interest in SiC Nano for PicoGeo. The main message conveyed given by the video is that improving the sensitivity of current strain meter technology – i.e., the goal of the Sic nano for PicoGeo project – is key to enhancing geoscience and geohazard monitoring, which directly affects the more excellent safety of the population in the earthquake and volcanic risk areas. </p>
ARCHIMEDES Project's Animated Video 'ARCHIMEDES: Pioneering a Sustainable Future'
<div> <p><span>The ARCHIMEDES project, a leading initiative in sustainable innovation, has launched an animated video titled "ARCHIMEDES: Pioneering a Sustainable Future." This video offers a detailed look into the project’s groundbreaking efforts to integrate sustainability with advanced technology across various sectors.</span></p> </div> <div> </div> <div> </div> <div> <p><span>ARCHIMEDES stands at the intersection of innovation and sustainability, aiming to revolutionize the future of mobility, energy, and safety within the framework of Society 5.0. The project focuses on developing state-of-the-art components, models, and methodologies to significantly improve the efficiency and lifespan of propulsion systems, power components, and energy storage devices.</span></p> </div> <div> </div> <div> </div> <div> <p><span>The video highlights how the ARCHIMEDES project spans multiple key industries:</span></p> </div> <div> <ul> <li> <p><span><strong>Automotive:</strong> Pioneering new propulsion systems to make vehicles more efficient and environmentally friendly.</span></p> </li> <li> <p><span><strong>Aviation:</strong> Enhancing energy efficiency and sustainability in the aerospace sector.</span></p> </li> <li> <p><span><strong>Industry:</strong> Transforming industrial processes to be more sustainable and cost-effective.</span></p> </li> </ul> </div> <div> </div> <div> </div> <div> <p><span>The ARCHIMEDES project is committed to creating a sustainable future by leveraging the latest innovations and technologies. By adopting an interdisciplinary approach, the project aims to be at the forefront of advancements in mobility, energy, and industrial processes. The vision is to not only meet current demands but also to anticipate and address future challenges.</span></p> </div> <div> </div> <div> </div> <div> <p><span>The newly released animated video provides a comprehensive overview of how ARCHIMEDES is leading the way toward a more sustainable future. The project invites viewers to join in this transformative journey.</span></p> </div>
Data from: An inexpensive and open-source method to study large terrestrial animal diet and behavior using time-lapse video and GPS
1. The behavior of free-ranging animals is difficult to study, especially on the large spatial and temporal scales relevant to long-lived large species. Animal-borne video and environmental data collection systems (AVEDs) record behavior and other data in real time as animals conduct daily activities. However, few studies have combined systematically collected, long term AVED foraging data with environmental and movement data to test hypotheses on animal foraging. Additionally, AVEDs are often either prohibitively expensive, or require extensive fabrication and programming knowledge. 2. The video and coordinate animal-mounted system (VACAMS) is an animal-mounted data collection system based on a modified GoPro® action camera platform that records short, first "person" perspective videos of animal behavior on an automated time-lapse schedule. As most videos are georeferenced, researchers can return to the locations of specific behaviors and collect accurate, fine-grained data on non-woody vegetation and other habitat characteristics that may influence animal behavior. Moreover, VACAMS are inexpensive and easy to use. 3. This study describes VACAMS preliminary data on cattle foraging and a hypothesis exploring free-ranging cattle browsing habits throughout the rainy season in the tropical dry forest of Sonora, Mexico. I generated a database of vegetation types consumed by cows each month (Annual, Woody, and Leaf litter) and compared actual vegetation type frequencies to a priori assumptions based on seasonal patterns of forage availability. During the monsoons, when palatable vegetation was abundant, frequencies of annual and woody perennial vegetation in cattle diets did not differ from month to month. When the rains ceased and palatable vegetation became scarce, cows switched to leaf litter, dead annual vegetation, twigs, and dried leguminous fruits. 4. Open source software and commercially available hardware make VACAMS financially attainable for many researchers, land managers, students, and other user groups. VACAMS could be used on a range of domestic and semi-domestic free-ranging animals, particularly in dense forests where conventional observations are impossible. With improvements to GPS battery life and durability, the weakest points of the system, VACAMS could also potentially apply to studies of other large terrestrial animals.
paperChain - Video Animation - Circular Case 2 (SPAIN)
<p>This animation video summarises in approximately two minutes the most relevant results of the implementation of paperChain's Circular Case.</p> <p> </p>
Storybook and Animation Video Adjuncts to Tell-Show-Do in Pediatric Dentistry
ClinicalTrials.gov study NCT07209696. IPD Sharing: NO. Countries: 0. Publications: 5.
Evaluation of the Effect of Animated Video-Assisted Nutrition Education on Heart Failure Patients
ClinicalTrials.gov study NCT07305272. IPD Sharing: YES. Countries: 1. Publications: 1.
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.