DocumentCode :
3161351
Title :
Bayesian fusion of laser and vision for multiple People Detection and tracking
Author :
Song, Xuan ; Cui, Jinshi ; Zhao, Huijing ; Zha, Hongbin
Author_Institution :
Key Lab. of Machine Perception (Minist. of Educ.), Peking Univ., Beijing
fYear :
2008
fDate :
20-22 Aug. 2008
Firstpage :
3014
Lastpage :
3019
Abstract :
We present a promising system to simultaneously detect and track multiple humans in the outside scene using laser and vision. The useful information of laser and vision is automatically extracted and combined in a Bayesian formulation. In order to compute MAP estimation, an effective probabilistic detection-based particle filter (PD-PF) has been proposed. Experiments and evaluations demonstrate that not only can our system perform robustly in real environments, but also obtain better approximation of MAP than previous methods in most complex situations.
Keywords :
estimation theory; object detection; particle filtering (numerical methods); sensor fusion; target tracking; Bayesian fusion; MAP estimation; multiple people detection; multiple people tracking; probabilistic detection-based particle filter; Bayesian methods; Data mining; Face detection; Humans; Laser fusion; Layout; Particle filters; Proposals; Robustness; Target tracking; Bayesian estimation; Multi-target tracking; Sensor fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE Annual Conference, 2008
Conference_Location :
Tokyo
Print_ISBN :
978-4-907764-30-2
Electronic_ISBN :
978-4-907764-29-6
Type :
conf
DOI :
10.1109/SICE.2008.4655180
Filename :
4655180
Link To Document :
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