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34 results for “camera systems”
Evolution of IT system and TEM camera performance
<p>This Excel file collates throughput specifications of transmission electron microscopy (TEM) cameras, mass storage, network and memory between 1996 and 2018. The absolute and relative development of the throughput is analyzed in charts.</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>
The processing results, dataset and original codes of Coral reef PtCloud segmentation model (based on proposed underwater camera systems)
<p><strong># Data Introduction</strong><br>The proposed camera system includes three operation modes: Surface Mode, Horizontal Mode, and Curved Mode.</p> <ul> <li><strong>Surface Mode</strong>: Provides 3D reconstructions (point cloud), DEM, and orthophoto maps of the seabed (covering a line of 70m in length).</li> <li><strong>Horizontal Mode</strong>: Provides 3D reconstructions (point cloud and mesh) and orthophoto maps of a single transect line.</li> <li><strong>Curved Mode</strong>: Offers 3D reconstructions (mesh) of various targets, including artificial coral reefs, coral reefs with snails, and coral reefs with starfish.</li> </ul> <p>All mesh results are saved in <code>.FBX</code> format, and point cloud results are saved in <code>.TXT</code> format.</p> <p><strong># Code Introduction</strong><br>The backbone of our point cloud segmentation model is the KPConv model.<br>If you encounter any issues during code deployment, please refer to the original KPConv repository (<a href="https://github.com/HuguesTHOMAS/KPConv" target="_new" rel="noopener">Original Code: https://github.com/HuguesTHOMAS/KPConv</a>).<br>We provide our modified code (customized for our task) along with the complete point cloud dataset.</p>
Associated raw data to the PhD thesis: Design and evaluation of a camera-based indoor positioning system for forklift trucks
<p>This is a test data set for marker-based augmented reality algorithms used to locate ground conveyors in an industrial environment. It was recorded in the testing area of the chair fml at TUM to develop and evaluate algorithms for locating forklift trucks in my PhD thesis "Entwicklung und Evaluierung einer kamerabasierten Lokalisierungsmethode für Flurförderzeuge" (see https://mediatum.ub.tum.de/?id=1395267 available in German only).</p>
FIGURE 3 in COMPUTER-AIDED DRAWING SYSTEM - SUBSTITUTE FOR CAMERA LUCIDA Ekaterina A. S and Dmitry D. V
FIGURE 3: Setting a live image from the camera as the background for drawing (software used for this example are VLC media player and GIMP graphic software). Since the overlay mode image cannot be reproduced in a screenshot, we photographed the computer screen using a digital camera instead of making the combined images from incomplete screenshots: A – media player showing the image; B – screenshot taken from A and pasted to the new file in the drawing software. The overlay mode is active: part of the video frame is visible through a replica of the media player's window where it overlaps with an original window of the media player, the rest of the replica is dark but is nevertheless filled with overlay color. Both arrows point to the area filled with overlay color; C – media player is closed, the whole area filled with overlay color looks dark; D – same as C, but the media player was not in overlay mode when the screenshot was taken. There is no overlay color on the screen. See text for further explanations.
FIGURE 2 in COMPUTER-AIDED DRAWING SYSTEM - SUBSTITUTE FOR CAMERA LUCIDA Ekaterina A. S and Dmitry D. V
FIGURE 2: Settings of VLC media player. Those important for correct and convenient work in overlay mode are indicated by arrows. This dialog can be found under the 'Tools> Preferences' menu.
FIGURE 1 in COMPUTER-AIDED DRAWING SYSTEM - SUBSTITUTE FOR CAMERA LUCIDA Ekaterina A. S and Dmitry D. V
FIGURE 1: An example of a working place with the complete drawing apparatus ready to use. C-camera, T-pen tablet
FIGURE 4 in COMPUTER-AIDED DRAWING SYSTEM - SUBSTITUTE FOR CAMERA LUCIDA Ekaterina A. S and Dmitry D. V
FIGURE 4: The procedure of setting the video camera as a source of live capture image in VLC media player: A – click 'Open capture device' under 'Media' menu; B – choose the video camera ('Video device name'), set 'Audio device name' to 'None' and set the horizontal pixel size of the video image — it must be chosen from the predefined list specific for particular video camera or, alternatively, left blank. In the latter case the video, most probably, will have the lowest possible resolution. The bottom arrow points to the command line string which is generated by VLC media player and which can be used to automate the procedure of setting the video camera parameters; this command line is not required for the method described in this paper; C – setting the live capture image as a desktop background for convenient drawing.
Data from: A high-resolution panorama camera system for monitoring colony-wide seabird nesting behaviour
1. Obtaining accurate and representative demographic metrics for animal populations is critical to many aspects of wildlife monitoring and management. However, at remote animal colonies, metrics derived from sequential counts or other continuous monitoring are often subject to logistical, weather and disturbance challenges.The development of remote camera technologies has assisted monitoring, but limitations in spatial and temporal resolution and sample sizes remain. 2. Here we describe the application of a robotic camera system (Gigapan) which takes a tiled sequence of photographs that are automatically stitched together to form high-resolution panoramas. We demonstrate the application of the Gigapan using data collected during field-testing at a shy albatross colony on Albatross Island in northwest Tasmania. 3. We took daily panoramas over five days to estimate mean incubation shift-duration, an indirect measure for foraging trip duration, in an existing study area. Similar numbers of occupied nests could be observed at a distance of ~100m in the Gigapan panoramas compared to ground-based counts (115 and 117 respectively). Of these, birds on 90% of nests visible in the panoramas could be unambiguously identified as marked or unmarked with a small daub of paint throughout the study period and thus a shift change reliably recorded. Gigapan-based shift duration was estimated using a novel instantaneous statistical method and were longer than estimates earlier in the egg brooding period, potentially revealing a new pattern in shift duration. 4. This example field application provides proof-of-concept and demonstration that the relatively low cost Gigapan system provides the spatial advantages of satellite or aerial photos with the detail and temporal replication of land-based camera systems. The Gigapan system can extend or enhance traditional data collection methods, particularly for simultaneous observations, at distance, of the behaviour of many surface nesting colonial seabirds..
Breathing Rate and Heart Rate Dataset using Integrated mmWave FMCW Radar and Camera Steering System
<p>The presented dataset consists of raw and transformed CWT images of the breathing and heart waveforms obtained from a radar<br> and IP camera setup. The setup is a self-proposed setup with a mmWave radar mounted over an IP camera and can capture<br> the breathing and heart waveforms of the person in the room in front of the system in any orientation. The dataset can be used to estimate the vital signs using any machine learning model and important information about the respiration rate and pulse rate<br> can then be obtained. The dataset is a total of 1280 images- 720 raw and 720 processed. The processed dataset is labeled in six different classes. The first bifurcation is between breath and heart, breath signal is classified as low, normal, and high whereas the heart signal is classified as low, normal, and slightly low. The subject is oriented in differently so that the setup can steer towards the person and capture the breath and heart signals accordingly.</p>
Supplemental Video 1 to Vanzella et al paper: A passive, camera-based head-tracking system for real-time, three-dimensional estimation of head position and orientation in rodents
<p>This video shows how the head tracker described in the manuscript "<strong>A passive, camera-based head-tracking system for real-time, three-dimensional estimation of head position and orientation in rodents" </strong>can track in real time the pose of the head of rat engaged in a perceptual discrimination task.</p>
Data from: A high-resolution panorama camera system for monitoring colony-wide seabird nesting behaviour
Open the record for dataset details and reuse information.
[Videos] Design of resilient smart highway systems with data-driven monitoring from networked cameras
<p>Traditional high-way transportation systems are monitored based on traffic counters. Such sensors provide much less information compared to traffic cameras and make the system less secure/resilient to attacks/disasters. Thanks to the success of deep learning for object detection/segmentation on images and the publicly available large-scale image datasets with object labels, fusing the information from both traffic counters and traffic cameras has the potential to improve the security and resilience of existing high- way transportation systems. The purpose of the project is to investigate such a potential by developing a deep-learning-based highway video monitoring method that can reliably estimate the fine-grained (car/truck/motorcycle) traffic flow of a high-way network. First, we need to collect a large- scale traffic video dataset with traffic flow estimations from corresponding traffic counters. Then, we need to find efficient deep learning methods for extracting fine-grained local traffic information from individual traffic videos. At last, we need to correlate this information with traffic counters for sensor fusion and detection of defective counters.</p>
A Comparison of Machine-Learning Assisted Optical and Thermal Camera Systems for Beehive Activity Counting
Open the record for dataset details and reuse information.
Pomacea canaliculata eye: a new system to study full camera-type eye regeneration [regeneration time-course]
GEO Series GSE240083. Pomacea canaliculata. 36 samples. Type: Expression profiling by high throughput sequencing.
Pomacea canaliculata eye: a new system to study full camera-type eye regeneration [oral tentacles, cephalic, tentacles, eye stalks and extracted retinas]
GEO Series GSE243241. Pomacea canaliculata. 12 samples. Type: Expression profiling by high throughput sequencing.
Pomacea canaliculata eye: a new system to study full camera-type eye regeneration [embryonic development time-course]
GEO Series GSE240084. Pomacea canaliculata. 34 samples. Type: Expression profiling by high throughput sequencing.
Initial camera matrix values for AWI CANON aerial imaging system
<p>The file contains a camera matrix in Agisoft Metashape's format that can be used as initial parameters for a multi view reconstruction of aerial sea ice images recorded with the AWI CANON 14mm wide-angle camera (sensor.awi.de ID 4430). </p>
Portable Endoscopic Camera System Using Modified Action Camera for Endoscopic Sinunasal Examination
ClinicalTrials.gov study NCT07289854. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparison of Non-mydriatic Camera Systems in a Female Health Hospital
ClinicalTrials.gov study NCT02089009. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.