DocumentCode
2155651
Title
Graph-based sequential particle filtering in lossy networks: Single and multiple collaborative cameras
Author
Huang, Jing ; Schonfeld, Dan
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Chicago, Chicago, IL, USA
fYear
2011
fDate
22-27 May 2011
Firstpage
1189
Lastpage
1192
Abstract
This paper presents a novel approach of multiple target tracking from multiple collaborative cameras. Firstly, particle filtering for conditional density propagation on graphs to address missing frames from one view is introduced. The Markov Properties and Separation Theorem are used to derive an exact solution for estimation on graphs with missing frames. Furthermore, a distributed multiple target tracking solution from multiple cameras is proposed by using collaborative particle filters. With epipolar geometry constraint, camera collaboration message is delivered between different views by particles. Results demonstrate that our system can deal with missing frames in the presence of occlusions.
Keywords
Markov processes; graph theory; particle filtering (numerical methods); target tracking; video cameras; Markov properties; camera collaboration message; conditional density propagation; distributed multiple target tracking solution; epipolar geometry constraint; graph-based sequential particle filtering; lossy networks; multiple collaborative cameras; separation theorem; single collaborative cameras; Cameras; Collaboration; Geometry; Graphical models; Hidden Markov models; Markov processes; Target tracking; Graphical models; Missing frames; Multi-camera; Occlusion; Particle filtering;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location
Prague
ISSN
1520-6149
Print_ISBN
978-1-4577-0538-0
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2011.5946622
Filename
5946622
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