DocumentCode :
1312521
Title :
Crowd Density Analysis with Marked Point Processes [Applications Corner]
Author :
Ge, Weina ; Collins, Robert T.
Author_Institution :
Comput. Sci. & Eng. Dept., Penn State Univ., University Park, PA, USA
Volume :
27
Issue :
5
fYear :
2010
Firstpage :
107
Lastpage :
123
Abstract :
This article presents a Bayesian approach that estimates the count and location of individuals in a video frame. Crowds are modeled by a marked point process (MPP) that couples a spatial stochastic process governing number and placement of individuals with a conditional mark process for selecting body size, shape, and orientation. Given a noisy, binary mask image where pixels are labeled foreground or background, the approach seeks a configuration of cutout shapes that simultaneously "covers" as many foreground pixels and as few background pixels as possible.
Keywords :
stochastic processes; video signal processing; video surveillance; Bayesian approach; crowd density analysis; marked point processes; spatial stochastic process; video frame; Gaussian distribution; Legged locomotion; Pixel; Proposals; Prototypes; Surveillance; Video equipment;
fLanguage :
English
Journal_Title :
Signal Processing Magazine, IEEE
Publisher :
ieee
ISSN :
1053-5888
Type :
jour
DOI :
10.1109/MSP.2010.937495
Filename :
5562669
Link To Document :
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