상세정보
학술지
Robust Multi-person Tracking for Real-Time Intelligent Video Surveillance
- 발행일
- 201506
- 출처
- ETRI Journal, v.37 no.3, pp.551-561
- ISSN
- 1225-6463
- 출판사
- 한국전자통신연구원 (ETRI)
- 협약과제
- 13VS1100, 사람에 의한 안전위협의 실시간 인지를 위한 능동형 영상보안 서비스용 원거리 (CCTV 주간환경 5m이상) 사람 식별 및 검색 원천기술 개발, 유장희
- 초록
- 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 제안 키워드
- Background Modeling, Data association, Multi-person tracking, Multiple object tracking, Object tracking algorithm, Real-Time, Region Of Interest(ROI), Two-Step, computation time, intelligent video surveillance, particle filtering