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Optical Engineering • Open Access

Object tracking using an adaptive Kalman filter combined with mean shift
Author(s): Xiaohe Li; Taiyi Zhang; Xiaodong Shen; Jiancheng Sun

Paper Abstract

An object tracking algorithm using an adaptive Kalman filter (KF) combined with mean shift (MS) is proposed. First, the system model of KF is constructed, then the center of the object predicted by KF is used as the initial value of the MS algorithm. The searching result of MS is fed back as the measurement of the adaptive KF, and the estimate parameters of KF are adjusted by the Bhattacharyya coefficient adaptively. The proposed method has the robust ability to track a moving object in consecutive frames under certain real-world complex situations, such as a moving object disappearing partially or totally due to occlusion, fast moving objects, and sudden changes in velocity of a moving object. The experimental results demonstrate that the proposed tracking algorithm is robust and practical.

Paper Details

Date Published: 1 February 2010
PDF: 3 pages
Opt. Eng. 49(2) 020503 doi: 10.1117/1.3327281
Published in: Optical Engineering Volume 49, Issue 2
Show Author Affiliations
Xiaohe Li, Xi'an Jiaotong Univ. (China)
Taiyi Zhang, Xi'an Jiaotong Univ. (China)
Xiaodong Shen, Xi'an Jiaotong Univ. (China)
Jiancheng Sun, Jiangxi Univ. of Finance and Economics (China)


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