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18 results for “Camera calibration”
Mars 2020 Perseverance SHERLOC WATSON camera pre-delivery characterization and calibration image data
<p>The data presented here include images acquired by the WATSON (Wide Angle Topographic Sensor for Operations and eNgineering) camera during pre-delivery characterization and calibration testing at Malin Space Science Systems (MSSS, San Diego, California, USA) in September and October 2019. They also include video documentation of the camera’s dust cover motion. WATSON is one of two imaging subsystems of the SHERLOC (Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals) instrument onboard NASA’s Mars 2020 Perseverance rover which landed in Jezero crater, Mars, in February 2021.</p> <p>These data accompany the instrument calibration and characterization report by Edgett et al. (2019) and the WATSON characteristics reported by Bhartia et al. (2021). The image data presented here are listed and described in the Appendix to Edgett et al. (2019), which is also available here with the data.</p> <p>References cited:</p> <p>Bhartia, R., L. W. Beegle, L. DeFlores, W. Abbey, J. Razzell Hollis, K. Uckert, B. Monacelli, K. S. Edgett, M. R. Kennedy, M. Sylvia, D. Aldrich, M. Anderson, S. A. Asher, Z. Bailey, K. Boyd, A. S. Burton, M. Caffrey, M. J. Calaway, R. Calvet, B. Cameron, M. A. Caplinger, B. L. Carrier, N. Chen, A. Chen, M. J. Clark, S. Clegg, P. G. Conrad, M. Cooper, K. N. Davis, B. Ehlmann, L. Facto, M. D. Fries, D. H. Garrison, D. Gasway, F. T. Ghaemi, T. G. Graff, K. P. Hand, C. Harris, J. D. Hein, N. Heinz, H. Herzog, E. Hochberg, A. Houck, W. F. Hug, E. H. Jensen, L. C. Kah, J. Kennedy, R. Krylo, J. Lam, M. Lindeman, J. McGlown, J. Michel, E. Miller, Z. Mills, M. E. Minitti, F. Mok, J. Moore, K. H. Nealson, A. Nelson, R. Newell, B. E. Nixon, D. A. Nordman, D. Nuding, S. Orellana, M. Pauken, G. Peterson, R. Pollock, H. Quinn, C. Quinto, M. A. Ravine, R. D. Reid, J. Riendeau, A. J. Ross, J. Sackos, J. A. Schaffner, M. Schwochert, M. O Shelton, R. Simon, C. L. Smith, P. Sobron, K. Steadman, A. Steele, D. Thiessen, V. D. Tran, T. Tsai, M. Tuite, E. Tung, R. Wehbe, R. Weinberg, R. H. Weiner, R. C. Wiens, K. Williford, C. Wollonciej, Y.-H. Wu, R. A. Yingst, J. Zan (2021) Perseverance’s Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) investigation, Space Science Reviews 217, 58. https://doi.org/10.1007/s11214-021-00812-z</p> <p>Edgett, K. S., M. A. Caplinger, M. A. Ravine (2019) Mars 2020 Perseverance SHERLOC WATSON Camera Pre-delivery Characterization and Calibration Report, Malin Space Science Systems, San Diego, California. https://doi.org/10.13140/RG.2.2.18447.00165</p>
Camera-IMU calibration with rolling shutter camera
<p>This video illustrates the performance of the proposed rolling shutter camera-IMU calibration. A checkerboard is used to help the monocular camera recover the scale so that the relative translation can also be calibrated.</p> <p>The red pluses show the detected checkerboard corners, while the green squares show the projection using the filtered camera pose.</p> <p>As can be seen, in the case of motion blur, the detected corners may not be accurate with some drifts, while the projected corners are still close to the real corners.</p>
On the use of a consumer-grade 360-degree camera as a radiometer for scientific applications: calibration dataset
<p>Studying the geometric distribution of the light field in terms of absolute radiometry required expensive and complex instruments. New types of compact 360-degree cameras have recently appeared on the consumer technology market. Some of these allow users to access raw imagery, offering sensor-level data that can be directly exploited for absolute light quantification. This paves the way for easy-to-use, inexpensive and accessible radiance cameras that can be operated in a wide range of natural environments. </p> <p>This dataset presents raw format images captured with the camera Insta360 ONE for its calibration and characterization. These experiments include geometric calibration, relative illumination evaluation, spectral response determination, absolute spectral radiance calibration, as well as linearity and dark frame analysis. In addition, we are providing data from a calibration validation experiment based on co-located measurements of the sky's downward radiance using a 360-degree calibrated camera and a scientific radiometer: the Compact Optical Profiling System (C-OPS, Biospherical Instruments Inc.).</p> <p>This repository contains raw files as taken by the camera's imaging sensor. In most cases, no data processing has been carried out. The entire data set is contained in a .zip file which includes the following sub-folders (in alphabetical order):</p> <ul> <li><strong>absolute-radiance</strong>: data (.dng, .tsv , .hdf5) acquired for <em>absolute spectral radiance</em> calibration</li> <li><strong>darkframe: </strong>DNG raw images taken for <em>dark frame</em> analysis</li> <li><strong>geometric: </strong>DNG images used for the <em>geometric calibration</em></li> <li><strong>immersion-factor: </strong>DNG images for the calculation of the immersion factor</li> <li><strong>linearity:</strong> DNG images for <em>linearity</em> assessment (gain and exposure time)</li> <li><strong>relative-illumination: </strong>DNG images for <em>roll-off (relative illumination) </em>characterization</li> <li><strong>relative-spectral-response: </strong>data (.asc, .dng) taken for relative spectral response characterization</li> <li><strong>verification&validation: </strong>time series data (.tsv, .dng) of the calibration validation experiment </li> </ul> <p>Each folder contains a <strong>README </strong>file explaining the additional subfolders and their files. As you may notice, some of the subfolders are named "lensclose" or "lensfar". They refers to the data acquired with the fish-eye optic assembly that is closer or farther from the top of the 360-degree camera respectively. Some calibrations were performed both in water and in air (geometric calibration, relative-illumination). In that regard, the images were placed in folders refering to "air" and "water". The routines (coded in python) for the data processing can be found in the following <a href="https://github.com/RaphaelLarouche/radiance_camera_insta360/tree/master_v01">Github repository</a> (master_v01) or the <a href="../records/4660994">Zenodo stored version</a>. The useful scripts are located in the <em>calibration</em> directory, and the<strong> README</strong> for each folder points to the revelant code for analysis of the files they contain. For additional information, all the methodologies are described in the <a href="https://arxiv.org/abs/2305.07103">arXiv preprint</a>. </p>
Crowdsourced dataset of firefly trajectories obtained by automated stereo calibration of 360-degree cameras
<p>Advancements in animal tracking techniques, spanning from migrating mammals to swarming insects, have resulted in remarkable progress in the fields of behavioral ecology and conservation science. Recently, we have devised a method for tracking luminous fireflies in their natural habitat using stereoscopic pairs of 360-degree cameras. This method offers affordability, versatility, and ease of setup; however, the process of camera calibration has remained tedious and time-consuming. Now, we have introduced an enhanced algorithm that achieves spatial and temporal stereo calibration directly from the data, eliminating the need for manual procedures both in the field and during video processing. The algorithm relies on cross-correlation of flashing patterns and numerical estimation of camera pose. Utilizing this improved protocol and processing software, we have compiled an extensive dataset comprising over 100 reconstructed firefly swarms of various species. This data was gathered throughout the United States by numerous contributors following a straightforward protocol. The dataset holds significant potential for advancing our comprehension of firefly collective behavior, facilitating population monitoring, and expanding citizen science initiatives.</p>
Crowdsourced dataset of firefly trajectories obtained by automated stereo calibration of 360-degree cameras
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Data and Code from: Multi-camera calibration with pattern rigs, including for non-overlapping cameras: CALICO
<p>This record contains the data used in the paper, "Multi-camera calibration with pattern rigs, including for non-overlapping cameras: CALICO", and a link to the corresponding code for calibration of camera networks. The full method and a description of the dataset is given in the companion paper, currently on arXiv: https://arxiv.org/abs/1903.06811 .</p><p>And the code is on Github: https://github.com/amy-tabb/calico</p><p> </p>
Data from: Selection of appropriate multispectral camera exposure settings and radiometric calibration methods for applications in phenotyping and precision agriculture
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GONet v2 camera calibration
<p>The following dataset contains images taken by the GONet All sky camera for the "GONet All sky camera calibration" LICA report.</p>
Eurex-LUNa Abisko Trials Stereo Camera Calibration
<p>Bottom Stereo Camera Calibration Images for AUV Deepleng. They should be used for both determining intrinsic as well as extrinsic calibration parameters for the bottom-looking stereo camera. This is necessary for the image data published with DOI 10.5281/zenodo.7035119 .</p> <p>Contact: tom.creutz@dfki.de, bilal.wehbe@dfki.de</p> <p> </p> <p>Funded by BMWi (Kennziffer 50 NA 2002)</p>
LiDAR-camera calibration dataset
<p>This dataset provides several LiDAR-camera data sequences recorded in the rosbag2 format to test LiDAR-camera extrinsic calibration algorithms. The ros2 bag files were recorded with two LiDAR-camera configurations (LiDAR: Livox Avia / Ouster OS1-32, camera: STC-MCS500POE).</p> <p>livox.tar.gz contains five rosbags with the following topics:</p> <ul> <li>Topic: /livox/points | Type: sensor_msgs/msg/PointCloud2 |</li> <li>Topic: /livox/imu | Type: sensor_msgs/msg/Imu |</li> <li>Topic: /livox/lidar | Type: livox_interfaces/msg/CustomMsg |</li> <li>Topic: /image | Type: sensor_msgs/msg/Image |</li> <li>Topic: /camera_info | Type: sensor_msgs/msg/CameraInfo |</li> </ul> <p><br> ouster.tar.gz contains two rosbags with the following topics:</p> <ul> <li>Topic: /camera_info | Type: sensor_msgs/msg/CameraInfo |</li> <li>Topic: /image | Type: sensor_msgs/msg/Image |</li> <li>Topic: /points | Type: sensor_msgs/msg/PointCloud2 |</li> </ul> <p><br> </p>
Calibration Data for "Sycamore" instrument in Lee Lab, Cambridge; Prime95B sCMOS cameras, Gain 3
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Non-Overlapping Multi-Camera Calibration Dataset using Icosahedron and Cube Calibration Object
<p>Our dataset comprises images captured using two 3D calibration objects: an icosahedron and a cube. Six 20MP monochrome cameras were arranged in a semicircular configuration with minimal overlapping fields of view. A consistent robotic motion pattern was employed to acquire sequential images for both calibration objects.</p> <p>This work is conducted at the Institute for Factory Automation and Production Systems(<a href="https://www.faps.fau.eu/">FAPS</a>), University of Erlangen-Nuremberg, Germany.</p>
The Camera Oximeter: A Calibration Study
ClinicalTrials.gov study NCT01732016. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Polar Visible Imaging System (VIS) Low Resolution Camera Images, Calibrated, Level 0 (L0), 12 s Data
Instrument Functional Description: The VIS Instrument is a Set of three Low Light Level Cameras. Two of these Cameras share primary and some secondary Optics and are designed to provide Images of the Nighttime Auroral Oval at Visible Wavelengths. A Third Camera is used to monitor the Directions of the Fields-of-View of the Auroral Cameras with respect to the sunlit Earth and return Global Images of the Auroral Oval at Ultraviolet Wavelengths. The VIS Instrumentation produces an Auroral Image of 256 × 256 Pixels approximately every 24 s dependent on the Integration Time and Filter selected. The Fields-of-View of the two Nighttime Auroral Cameras are 5.6 × 6.3° and 2.8 × 3.3° for the Low and Medium Resolution Cameras, respectively. The Medium Resolution Camera was never activated. One or more Earth Camera Images of 256 × 256 Pixels are produced every 5 min, depending on the commanded Mode. The Field-of-View of the Earth Camera is approximately 20 × 20°. See: http://vis.physics.uiowa.edu/vis/vis_description/vis_description.htmlx Reference: Frank, L.A., J.B. Sigwarth, J.D. Craven, J.P. Cravens, J.S. Dolan, M.R. Dvorsky, J.D. Harvey, P.K. Hardebeck, and D. Muller, The Visible Imaging System (VIS) for the Polar Spacecraft, Space Science Review, Vol. 71, pp. 297-328, 1995. Data Set Description: The VIS Earth Camera Data Set comprises all Earth Camera Images for the selected Time Period. Full Coordinate Information is included for Viewer Orientation. In addition, a Rotation Matrix and a Table of Distortion-correcting Look Direction Unit Vectors are provided for the Purpose of calculating Coordinates for every Pixel. To facilitate viewing of the Images, a Mapping of Pixel Value to a recommended Color Table based on the Characteristics of the selected Filter will be included with each Image. A Relative Intensity Scale is provided through an Uncompressed Count Table. Approximate Intensity Levels in kiloRayleighs are given in an Intensity Table. For detailed Information on Intensities, see Sensitivities_and_Intensities.txt at https://cdaweb.gsfc.nasa.gov/Polar_VIS_docs/SENSITIVITIES_AND_INTENSITIES.TXT. Supporting Software is available at: http://vis.physics.uiowa.edu/vis/software/ Included is an IDL Program that displays the Images with the recommended Color Bar, provides approximate Intensities, Coordinate Data for each Pixel, and includes multiple Options for Image Manipulation.
Polar Visible Imaging System (VIS) Earth Camera Images, Calibrated (E0), 4 min Data
Instrument Functional Description: The VIS Instrument is a Set of three Low Light Level Cameras. Two of these Cameras share primary and some secondary Optics and are designed to provide Images of the Nighttime Auroral Oval at Visible Wavelengths. A Third Camera is used to monitor the Directions of the Fields-of-View of the Auroral Cameras with respect to the sunlit Earth and return Global Images of the Auroral Oval at Ultraviolet Wavelengths. The VIS Instrumentation produces an Auroral Image of 256 × 256 Pixels approximately every 24 s dependent on the Integration Time and Filter selected. The Fields-of-View of the two Nighttime Auroral Cameras are 5.6 × 6.3° and 2.8 × 3.3° for the Low and Medium Resolution Cameras, respectively. The Medium Resolution Camera was never activated. One or more Earth Camera Images of 256 × 256 Pixels are produced every 5 min, depending on the commanded Mode. The Field-of-View of the Earth Camera is approximately 20 × 20°. See: http://vis.physics.uiowa.edu/vis/vis_description/vis_description.htmlx Reference: Frank, L.A., J.B. Sigwarth, J.D. Craven, J.P. Cravens, J.S. Dolan, M.R. Dvorsky, J.D. Harvey, P.K. Hardebeck, and D. Muller, The Visible Imaging System (VIS) for the Polar Spacecraft, Space Science Review, Vol. 71, pp. 297-328, 1995. Data Set Description: The VIS Earth Camera Data Set comprises all Earth Camera Images for the selected Time Period. Full Coordinate Information is included for Viewer Orientation. In addition, a Rotation Matrix and a Table of Distortion-correcting Look Direction Unit Vectors are provided for the Purpose of calculating Coordinates for every Pixel. To facilitate viewing of the Images, a Mapping of Pixel Value to a recommended Color Table based on the Characteristics of the selected Filter will be included with each Image. A Relative Intensity Scale is provided through an Uncompressed Count Table. Approximate Intensity Levels in kiloRayleighs are given in an Intensity Table. For detailed Information on Intensities, see Sensitivities_and_Intensities.txt at https://cdaweb.gsfc.nasa.gov/Polar_VIS_docs/SENSITIVITIES_AND_INTENSITIES.TXT. Supporting Software is available at: http://vis.physics.uiowa.edu/vis/software/ Included is an IDL Program that displays the Images with the recommended Color Bar, provides approximate Intensities, Coordinate Data for each Pixel, and includes multiple Options for Image Manipulation.
Calibration data for EMCCD Camera
<p>Example datasets for the calibration (coversion to photon numbers</p>
IceBridge DMS L0 Camera Calibration V001
This data set contains camera calibration reports for IceBridge Digital Mapping System (DMS) missions flown over Antarctica and Greenland.
Camera calibration parameters
<p>Camera calibration parameters (intrinsics,extrinsics and distortion) for the RGBD camera Astra and the RGBD camera Intel Realsense F200</p> <p>Format: OpencvStorage/xml</p> <p>Generated using Opencv calibration functions</p>
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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.