Robust Multi‐person Tracking for Real‐Time Intelligent Video Surveillance

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 computat...

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Bibliographic Details
Published inETRI journal Vol. 37; no. 3; pp. 551 - 561
Main Authors Choi, Jin‐Woo, Moon, Daesung, Yoo, Jang‐Hee
Format Journal Article
LanguageEnglish
Published Electronics and Telecommunications Research Institute (ETRI) 01.06.2015
한국전자통신연구원
Subjects
background modeling
Multiple‐object tracking
particle filter
pedestrian detection
real‐time applications
video surveillance applications
전자/정보통신공학
Online AccessGet full text
ISSN1225-6463
2233-7326
DOI10.4218/etrij.15.0114.0629

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Summary: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.
Bibliography:jwc@etri.re.kr
jhy@etri.re.kr
This work was partly supported by the ICT R&D program of the MSIP, Rep. of Korea (No. 10039149, Development of Basic Technology of Human Identification and Retrieval at Distance for Active Video Surveillance Service with Real‐time Awareness of Safety Threats) and (No. 13‐912‐06‐006, Development of the Filtering Technology for Objectionable Streaming Contents on Smart Platform).
Jin‐Woo Choi
daesung@etri.re.kr
and Jang‐Hee Yoo (corresponding author
are with the SW & Contents Research Laboratory, ETRI, Daejeon, Rep. of Korea.
Daesung Moon
G704-001110.2015.37.3.020
http://etrij.etri.re.kr/etrij/journal/article/article.do?volume=37&issue=3&page=551
ISSN:1225-6463
2233-7326
DOI:10.4218/etrij.15.0114.0629