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Journal Article
Robust Multi-person Tracking for Real-Time Intelligent Video Surveillance
- Authors
- Jin-Woo Choi, Daesung Moon, Jang-Hee Yoo
- Issue Date
- 2015-06
- Citation
- ETRI Journal, v.37, no.3, pp.551-561
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.
- KSP Keywords
- Background Modeling, Data association, Intelligent Video Surveillance, Multi-person tracking, Multiple object tracking, Object tracking algorithm, Region Of Interest, Two-Step, computation time, particle filtering, pedestrian detection