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.
References: 14
- Y. F. Peng, “Research on Moving Target Detection and Tracking Algorithms,” Wuhan University of Technology, 2010
- B. Sun, “Mobile Background under the Research on Moving Object Detection and Tracking Technology,” Electronic Measurement and Instrument, Vol. 3, pp. 206-210, 2014
- P. H. Tian, “Research on Moving Object Detection and Tracking in Video Image,” Chang’an University, 2013
- Y. H. Wang, “Research on Moving Target Detection and Tracking Algorithm based on OpenCV,” Hangzhou Dianzi University, 2016
- X. H. Lu and Z. K. Shi, “Based on Dynamic Template Matching of Air Moving Target Detection and Tracking Control,” Electronic Measurement and Instrument, Vol. 10, pp. 935-941, 2014
- B. H. Yuan and D. X. Zhang, “Detection and Tracking of Video Moving Objects based on OpenCV,” Application of Computer System, Vol. 5, pp. 90-93, 2014
- W. Yang and X. F. Bai, “An Improved Moving Object Detection and Tracking Method,” TV Technology, Vol. 1, pp. 180-182, 2016
- M. Y. Liu, “Research of Moving Object Detection and Tracking Algorithm,” Journal of Hebei United University (Natural Science Edition), Vol. 1, pp. 65-70, 2015
- X. F. Tong and Q. S. Liu, “Analysis of Sports Video,” Journal of Computer Science, Vol. 7, pp. 1242-1251, 2008
- S. W. Hai and G. J. Li, “Player Detection and Tracking in Sports Video,” Computer Engineering, Vol. 19, pp. 230-232, 2008
- H. I. Xu, “Sports Video Sequence of Moving Object based on IMM Tracking Algorithm,” Journal of Image and Graphics, Vol. 5, pp. 920-924, 2009
- Y. Jiang, “Research on the Motion Video Tracking Technology based on Meanshift Algorithm and Color Histogram Algorithm,” Journal of Soochow University (Engineering Science Edition), Vol. 2, pp. 33-36, 2012
- P. Qu and T. Kang, “Based on Underlying Visual Information of Sports Video Intelligent Analysis,” Journal of Sports Adult Education, Vol. 3, pp. 49-51, 2012
- Y. Xiu, “Research on Moving Target Tracking and Detection Algorithm in Volleyball Video,” Science and Technology Bulletin, Vol. 7, pp. 160-162, 2015
Please note : You will need Adobe Acrobat viewer to view the full articles. |