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Contour coding based rotating adaptive model for human detection and tracking in thermal catadioptric omnidirectional vision |
Applied Optics, Vol. 51, Issue 27, pp. 6641-6652 (2012)
http://dx.doi.org/10.1364/AO.51.006641
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Abstract
In this paper, we introduce a novel surveillance system based on thermal catadioptric omnidirectional (TCO) vision. The conventional contour-based methods are difficult to be applied to the TCO sensor for detection or tracking purposes due to the distortion of TCO vision. To solve this problem, we propose a contour coding based rotating adaptive model (RAM) that can extract the contour feature from the TCO vision directly as it takes advantage of the relative angle based on the characteristics of TCO vision to change the sequence of sampling automatically. A series of experiments and quantitative analyses verify that the performance of the proposed RAM-based contour coding feature for human detection and tracking are satisfactory in TCO vision.
© 2012 Optical Society of America
OCIS Codes
(110.2970) Imaging systems : Image detection systems
(110.3080) Imaging systems : Infrared imaging
(110.6820) Imaging systems : Thermal imaging
(100.3008) Image processing : Image recognition, algorithms and filters
(100.4999) Image processing : Pattern recognition, target tracking
ToC Category:
Imaging Systems
History
Original Manuscript: January 10, 2012
Revised Manuscript: August 20, 2012
Manuscript Accepted: August 28, 2012
Published: September 19, 2012
Virtual Issues
Vol. 7, Iss. 11 Virtual Journal for Biomedical Optics
Citation
Yazhe Tang and Youfu Li, "Contour coding based rotating adaptive model for human detection and tracking in thermal catadioptric omnidirectional vision," Appl. Opt. 51, 6641-6652 (2012)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-51-27-6641
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