Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (1): 288-397.doi: 10.23940/ijpe.19.01.p29.288297

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Moving Target Detection and Trackingbased on Camshift Algorithm and KalmanFilter in Sport Video

Baojun Zhang()   

  1. Department of Physical Education, Harbin Institute of Technology,Harbin, 150001, China
  • Revised on ; Accepted on
  • Contact: Zhang Baojun E-mail:baojunzhangbjz@sina.com
  • About author:Baojun Zhang received his M.S degree fromschool of physical education, Northeast Normal University.He is anassociate professorinHarbin Institute of Technology.His research interests includesports teaching and training.

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.

Key words: Sport Video, Kalman filter, Camshift algorithm, object detection and tracing