Volume 7 Number 9 (Sep. 2012)
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JSW 2012 Vol.7(9): 2000-2008 ISSN: 1796-217X
doi: 10.4304/jsw.7.9.2000-2008

An Object Tracking Algorithm Based on the "Current" Statistical Model and the Multi-Feature Fusion

Jinhua Wang1 , JieCao1, 2, Di Wu1, and Yabing Yu1
1College of Electrical and Information Engineering, Lanzhou University of Technology,Lanzhou, China
2Key Laboratory of Gansu Advanced Control for Industrial Processes,Lanzhou,China

Abstract—Aimed at accurary and real-time object tracking under complex background,an object tracking algorithm based on multi feature fusion is proposed. Feature points tracking is used to reduce the match time and improve the real-time of tracking; To overcome the inaccuracy of a single feature tracking, the object model is presented by the color and texture features. For the traditional "current" statistical model in maneuvering object tracking defects, an improved algorithm which combined with adaptive kalman filter (AKF) is proposed to improve the tracking accuracy. Experimental results show that the proposed method is effective and robust under complex background, the object is similar to each other, the target was partial occlusion and when the object is maneuvering.

Index Terms—object tracking; objective model; “current” statistical model; feature points; feature fusion

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Cite: Jinhua Wang, JieCao, Di Wu, and Yabing Yu, "An Object Tracking Algorithm Based on the "Current" Statistical Model and the Multi-Feature Fusion," Journal of Software vol. 7, no. 9, pp. 2000-2008, 2012.

General Information

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