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7 results for “Camera Sensitivities”
Physlight - Camera Spectral Sensitivity Curves - Winquist et al. (2022)
<p><strong>Source URL</strong>: <a href="https://github.com/quister/physlight/commit/20100bce85c75fb7389949508d319d640e5d2be3">https://github.com/quister/physlight/commit/20100bce85c75fb7389949508d319d640e5d2be3</a></p> <p>Spectral sensitivity curves of a number of cameras as measured with Weta Digital's 'lightsaber' system.</p>
Camera Spectral Sensitivity Database - Jiang et al. (2013)
<p><strong>Source URL</strong>: <a href="http://www.gujinwei.org/research/camspec/db.html">http://www.gujinwei.org/research/camspec/db.html</a><br> <strong>Source DOI</strong>: 10.1109/WACV.2013.6475015</p> <p>Camera spectral sensitivity functions relate scene radiance with captured RGB triplets. They are important for many computer vision tasks that use color information, such as multispectral imaging, and color constancy.</p> <p>We create a database of 28 cameras covering a variety of types. The database contains the spectral sensitivity functions for 28 cameras, including professional DSLRs, point-and-shoot, industrial and mobile phone camera. We use a spectrometer PR655 from Photo Research Inc., a light source and monochrometer combined with an integrating sphere to do the measurement. Each measurement starts from wavelength 400nm to 720nm in an interval of 10nm. Measured Sensitivities are normalized to 1 for RGB channels seperately. The database is in the form of a text file. Each entry starts with camera name and follows by measured spectral sensitivities in red, green and blue channel.</p>
"It was recorded on Sunday, morning of the 28th of September as some of the slower runners of the Berlin Marathon made it past Torstrasse near my flat. Iwas out to buy some bread for breakfast, but Iusually bring a camera and my Edirol R-1 recorder whenever Igo out. Since Iwas freshly returned to Berlin Iguess Iwas sensitive to the more antiquated sounds which still survive there, like that of the organ grinder. Iam generally interested in how human beings are replacing the presence of Nature with an artificial environment made entirely by human hands (and thus far more understandable, it is hoped). In this new Human Nature, the sounds of Nature are also Human made. Iwrite about these things, but Ialso use the sounds in my videos and my interactive and generative media work, so generally Iam wandering around building up my archive of media documents for use as material in future works." [Baruch/ gottlieb]17 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"It was recorded on Sunday, morning of the 28th of September as some of the slower runners of the Berlin Marathon made it past Torstrasse near my flat. Iwas out to buy some bread for breakfast, but Iusually bring a camera and my Edirol R-1 recorder whenever Igo out. Since Iwas freshly returned to Berlin Iguess Iwas sensitive to the more antiquated sounds which still survive there, like that of the organ grinder. Iam generally interested in how human beings are replacing the presence of Nature with an artificial environment made entirely by human hands (and thus far more understandable, it is hoped). In this new Human Nature, the sounds of Nature are also Human made. Iwrite about these things, but Ialso use the sounds in my videos and my interactive and generative media work, so generally Iam wandering around building up my archive of media documents for use as material in future works." [Baruch/ gottlieb]17
Daedalus 2 - NS1b - XIX CEA - High sensitivity camera
<p>Video of the PRO-AM colaboration -between the Dep. Astrofísica y CC. de la Atmosfera of the Universidad Complutese de Madrid and Daedalus project, Astroinova Asociation.</p> <p>Mission of an stratospheric balloon.</p> <p>The mission Daedalus 2, launched from Corral de Almaguer (Cuenca/Spain).</p> <p>It was recorded with a High sensitivity camera and a video recorder.</p> <p> </p>
Testing the precision and sensitivity of density estimates obtained with a camera-trap method revealed limitations and opportunities
<p>The use of camera traps in ecology helps affordably address questions about the distribution and density of cryptic and mobile species. The Random encounter model (REM) is a camera-trap method that has been developed to estimate population densities using unmarked individuals. However, few studies have evaluated its reliability in the field, especially considering that this method relies on parameters obtained from collared animals (<i>i.e.</i> average speed, in km/h), which can be difficult to acquire at low cost and effort. Our objectives were to (1) assess the reliability of this camera-trap method and (2) evaluate the influence of parameters coming from different populations on density estimates. We estimated a reference density of black bears (<i>Ursus americanus</i>) in Forillon National Park (Québec, Canada) using a spatial capture-recapture estimator based on hair-snag stations. We calculated average speed using telemetry data acquired from four different bear populations located outside our study area and estimated densities using the REM. The reference density, determined with a Bayesian spatial capture-recapture model, was 2.87 individuals/10km<sup>2</sup> [95% CI: 2.41–3.45], which was slightly lower (although not significatively different) than the different densities estimated using REM (ranging from 4.06–5.38 bears/10km<sup>2 </sup>depending on the average speed value used). Average speed values obtained from different populations had minor impacts on REM estimates when the difference in average speed between populations was low. Bias in speed values for slow-moving species had more influence on REM density estimates than for fast-moving species. We pointed out that a potential overestimation of density occurs when average speed is underestimated, i.e. using GPS telemetry locations with large fix-rate intervals. Our study suggests that REM could be an affordable alternative to conventional spatial capture-recapture, but highlights the need for further research to control for potential bias associated with speed values determined using GPS telemetry data.</p>
Testing the precision and sensitivity of density estimates obtained with a camera-trap method revealed limitations and opportunities
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Measuring Breathing Airflow Using a Heat Sensitive Camera (ThermFlow)
ClinicalTrials.gov study NCT05972161. IPD Sharing: NO. Countries: 1. Publications: 0.
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