Volume 5 Number 9 (Sep. 2010)
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JSW 2010 Vol.5(9): 966-973 ISSN: 1796-217X
doi: 10.4304/jsw.5.9.966-973

A General Framework for Multi-Human Tracking

Ahmed Ali, Kenji Terada
Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan

Abstract—The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human tracking. The key contribution of the work is to use fast calculation for mean shift algorithm to perform tracking for the cases when Kalman filter fails due to measurement error. Local density maxima in the difference image - usually representing moving objects - are outlined by a fast non-parametric mean shift clustering procedure. The proposed approach has the robust ability to track moving objects, both separately and in groups, in consecutive frames under some kinds of difficulties such as rapid appearance changes caused by image noise and occlusion.

Index Terms—Kalman Filter, Fast Mean Shift Algorithm, Human Tracking.


Cite: Ahmed Ali, Kenji Terada, "A General Framework for Multi-Human Tracking," Journal of Software vol. 5, no. 9, pp. 966-973, 2010.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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