ETRI-Knowledge Sharing Plaform

KOREAN
논문 검색
Type SCI
Year ~ Keyword

Detail

Journal Article Robust Multi-person Tracking for Real-Time Intelligent Video Surveillance
Cited 41 time in scopus Download 22 time Share share facebook twitter linkedin kakaostory
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
DOI
https://dx.doi.org/10.4218/etrij.15.0114.0629
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, Multi-person tracking, Multiple object tracking, Object tracking algorithm, Real-Time, Region Of Interest(ROI), Two-Step, computation time, intelligent video surveillance, particle filtering