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7 results for “360° camera”
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>
Dataset: Inferring Inherent Optical Properties of Sea Ice Using 360-Degree Camera Radiance Measurements
<p>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 the angular radiance distributions measured with the Insta360 ONE 360-degree camera in sea ice. We report vertical profiles of the light field structure at two sites reprensentative of distinct sea ice types: High Arctic multi-year ice and Chaleur Bay (Quebec, Canada) landfast first-year ice. </p> <p>This repository contains the radiometric data stored in <strong>Hierarchical Data Format (HDF5, h5)</strong> under the following names: </p> <ul> <li><strong><a href="https://zenodo.org/api/records/14263256/draft/files/oden-08312018-imf-fluo.h5/content" target="_blank" rel="noopener noreferrer">oden-08312018-imf-fluo.h5</a></strong></li> <li><strong><a href="https://zenodo.org/api/records/14263256/draft/files/baiedeschaleurs-03232022-imf-fluo.h5/content" target="_blank" rel="noopener noreferrer">baiedeschaleurs-03232022-imf-fluo.h5</a></strong></li> </ul> <p>The High Arctic dataset (<strong>oden-08312018-imf-fluo.h5</strong>) contains only one station, while the Chaleur Bay (<strong>baiedeschaleurs-03232022-imf-fluo.h5</strong>) has four that can be accessed using these tags: "station_1", "station_2", "station_3", "station_4". The radiance measurements at each depth are reported as 2-dimensionals arrays with the azimuth directions (0-359°, 1° resolution) as columns and the zenith directions (0-180°, 1° resolution) as lines. 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" target="_blank" rel="noopener">Github repository</a> (master_v01) or the <a href="https://zenodo.org/records/4660994" target="_blank" rel="noopener">Zenodo stored version</a>. </p> <p>The methodologies to carefully calibrated the 360-degree camera for radiometry purpose are described in this <a href="https://doi.org/10.1364/AO.524122" target="_blank" rel="noopener">pulibcation</a> and the raw calibration data can be found in this Zenodo <a href="https://zenodo.org/records/10278731" target="_blank" rel="noopener">repository</a>. </p> <p>Additionnal information on the fieldwork and the data analysis are described in the <a href="https://doi.org/10.31223/X5V955" target="_blank" rel="noopener">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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Evaluation of an Artificial Intelligence Algorithm Reducing Noise on Fast Whole-body Bone Tomoscintigraphy Acquisitions Recorded by a 360 Degree Cadmium-Zinc-Tellurid Camera
ClinicalTrials.gov study NCT06782438. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Radcliffe Camera - 360 Measurements (E,B)
Radcliffe Camera, Oxford, UK "The Radcliffe Camera is a building of Oxford University, England, designed by James Gibbs in neo-classical style and built in 1737–49 to house the Radcliffe Science Library." 360 Measurements - Preview (External, Black&White) SIAD REF : OX121 Source: Objaverse 1.0 / Sketchfab
Radcliffe Camera - 360 Measurements (E,C)
Radcliffe Camera, Oxford, UK "The Radcliffe Camera is a building of Oxford University, England, designed by James Gibbs in neo-classical style and built in 1737–49 to house the Radcliffe Science Library." 360 Measurements - Preview (External, Coloured) SIAD REF : OX121 Source: Objaverse 1.0 / Sketchfab
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