2012
DOI: 10.1145/2184319.2184337
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Real-time computer vision with OpenCV

Abstract: Mobile computer-vision technology will soon become as ubiquitous as touch interfaces.

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Cited by 333 publications
(175 citation statements)
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“…Our custom software was written in Python 2.7.11 (Python Software Foundation, available at http://www.python.org) and utilized OpenCV 2.4.11 (Pulli et al 2012). The software used a Gaussian mixture-based foreground-background segmentation algorithm (as implemented in cv2.BackgroundSubtractorMOG) to separate each video frame into the foreground (subject) and background (arena floor) and then fitted a contour to the outline of the segmented image of the subject (using cv2.…”
Section: Video Trackermentioning
confidence: 99%
“…Our custom software was written in Python 2.7.11 (Python Software Foundation, available at http://www.python.org) and utilized OpenCV 2.4.11 (Pulli et al 2012). The software used a Gaussian mixture-based foreground-background segmentation algorithm (as implemented in cv2.BackgroundSubtractorMOG) to separate each video frame into the foreground (subject) and background (arena floor) and then fitted a contour to the outline of the segmented image of the subject (using cv2.…”
Section: Video Trackermentioning
confidence: 99%
“…It is oriented to work with realtime applications, for this reason it is a really good option to use it in facial recognition [7], tracing movements and objects detecting tasks [8], and functionality on mobile devices [9]. The last of great importance and interest for the development of the proposed project.…”
Section: Artificial Vision and Opencvmentioning
confidence: 99%
“…The experiment is realized by using VC + + 6.0 and OpenCV [11] computer vision library to program in the win7.…”
Section: Experimental Verification and Analysismentioning
confidence: 99%