Video Tracking of Human with Occlusion Based on MeanShift and Kalman Filter

Abstract:

In order to accomplish tracking of moving objects requirements, and overcome the defect of occlusion in the process of tracking moving object, this paper presents a method which uses a combination of MeanShift and Kalman filter algorithm. MeanShift object tracking algorithm uses a histogram to describe the color characteristics of an object, and search the location of an image region that the color histogram is closest to the histogram of the object. Histogram similarity is defined in terms of the Bhattacharya coefficient. When the moving object is a large area blocked, the future state of moving object is estimated by Kalman filter. Experimental results verify that the proposed algorithm achieves efficient tracking of moving objects under the confusing situations.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 3672-3677
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.3672
• Online since: August 2013
• Authors: Bao Hong Yuan, De Xiang Zhang, Kui Fu, Ling Jun Zhang
• Keywords: Kalman Filter (KF), Mean-Shift, Object Tracking, Occlusion

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