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Moving Target Detection and Tracking based on Camshift Algorithm and Kalman Filter in Sport Video

Volume 15, Number 1, January 2019, pp. 288-297
DOI: 10.23940/ijpe.19.01.p29.288297

Baojun Zhang

Department of Physical Education, Harbin Institute of Technology, Harbin, 150001, China

(Submitted on October 19, 2018; Revised on November 17, 2018; Accepted on December 23, 2018)

Abstract:

With the rapid growth of the video data’s amount, how to efficiently retrieve useful information has become very urgent. As the base of video indexing and searching, video annotation has great significance for its application prospect and research value. In the semantic detection, moving object detection and tracing is the basis. In the paper, adaptive Gaussian Mixture Model is used to background model; Camshift and Kalman filter are used to trace the players and ball. The implement of the algorithms is all based on Visual C++ and Visual c#2008. OpenCV and Aforge.net class base are also used. Experimental result shows that the method annotates well.

 

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