DocumentCode
3022603
Title
OVVV: Using Virtual Worlds to Design and Evaluate Surveillance Systems
Author
Taylor, Geoffrey R. ; Chosak, Andrew J. ; Brewer, Paul C.
Author_Institution
ObjectVideo Inc., Reston
fYear
2007
fDate
17-22 June 2007
Firstpage
1
Lastpage
8
Abstract
Object video virtual video (OVVV) is a publicly available visual surveillance simulation test bed based on a commercial game engine. The tool simulates multiple synchronized video streams from a variety of camera configurations, including static, PTZ and omni-directional cameras, in a virtual environment populated with computer or player controlled humans and vehicles. To support performance evaluation, OVVV generates detailed automatic ground truth for each frame including target centroids, bounding boxes and pixel-wise foreground segmentation. We describe several realistic, controllable noise effects including pixel noise, video ghosting and radial distortion to improve the realism of synthetic video and provide additional dimensions for performance testing. Several indoor and outdoor virtual environments developed by the authors are described to illustrate the range of testing scenarios possible using OVVV. Finally, we provide a practical demonstration of using OVVV to develop and evaluate surveillance algorithms.
Keywords
image segmentation; video streaming; video surveillance; virtual reality; PTZ camera; automatic ground truth; bounding boxes; camera configuration; commercial game engine; indoor virtual environment; multiple synchronized video streams; object video virtual video; omnidirectional camera; outdoor virtual environment; pixel noise; pixel-wise foreground segmentation; radial distortion; static camera; surveillance system; target centroid; video ghosting; virtual world; visual surveillance simulation test bed; Automatic control; Cameras; Computational modeling; Computer simulation; Engines; Games; Surveillance; Testing; Virtual environment; Working environment noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location
Minneapolis, MN
ISSN
1063-6919
Print_ISBN
1-4244-1179-3
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2007.383518
Filename
4270516
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