DocumentCode :
443178
Title :
Fixed point probability field for complex occlusion handling
Author :
Fleuret, Françcois ; Lengagne, Richard ; Fua, Pascal
Author_Institution :
Ecole Polytechnique Federale de Lausanne, Switzerland
Volume :
1
fYear :
2005
fDate :
17-21 Oct. 2005
Firstpage :
694
Abstract :
In this paper, we show that in a multi-camera context, we can effectively handle occlusions in real-time at each frame independently, even when the only available data comes from the binary output of a simple blob detector, and the number of present individuals is a priori unknown. We start from occupancy probability estimates in a top view and rely on a generative model to yield probability images to be compared with the actual input images. We then refine the estimates so that the probability images match the binary input images as well as possible. We demonstrate the quality of our results on several sequences involving complex occlusions.
Keywords :
hidden feature removal; image processing; real-time systems; actual input image; binary input image; blob detector; complex occlusion handling; fixed point probability; multicamera system; multiview multipeople detection; occupancy probability estimation; probability image; real-time system; Bayesian methods; Cameras; Computer vision; Detectors; Hidden Markov models; Image segmentation; Impedance matching; Probability distribution; Robustness; Yield estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
ISSN :
1550-5499
Print_ISBN :
0-7695-2334-X
Type :
conf
DOI :
10.1109/ICCV.2005.102
Filename :
1541321
Link To Document :
بازگشت