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TRACKING MULTIPLE PERSONS BASED ON ATTRIBUTED RELATIONAL GRAPH.

Authors :
WAN, QIN
WANG, YAONAN
YU, HONGSHAN
YUAN, XIAOFANG
LU, JUAN
Source :
International Journal of Pattern Recognition & Artificial Intelligence. Aug2011, Vol. 25 Issue 5, p713-739. 27p. 9 Color Photographs, 1 Diagram, 3 Charts, 6 Graphs.
Publication Year :
2011

Abstract

The appearance model is very effective in tracking multiple persons. The main difficulty in tracking persons is to represent appearance reliably and effectively, especially in the presence of occlusions. In this paper, an effective Attributed Relational Graph (ARG) based tracking algorithm is presented to track multiple persons even under occlusions. The appearance of each person is expressed by an ARG model which not only combines color feature with spatial information but also illustrates the relations among body parts. The similarity of ARG models is computed to build a matching matrix in consecutive frames. Four tracking situations are determined according to the matching matrix. In addition, to track persons under occlusions, probabilistic relaxation labeling in the ARG models of body parts is deduced to label occluded persons optimally. Experimental validation of the proposed tracking method is verified and presented on indoor and outdoor sequences. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02180014
Volume :
25
Issue :
5
Database :
Academic Search Index
Journal :
International Journal of Pattern Recognition & Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
64458954
Full Text :
https://doi.org/10.1142/S0218001411008646