Analysis of Multiple Object Detection using Kalman Filter in Sports Video

Abstract

Object detection and tracking on Broadcast Sports Video (BSV) plays an important role in content analysis and also it's a challenging task because of playing track, play court, player's size, noises, disturbances and occlusion in a playing court which fails the results of detection. In addition, occlusion of multiple players in matches also causes a failure of tracking. In this paper, an comprehensive study of a robust technique for object detection and player tracking using a Kalman filter(KF) has elaborated. The parameters of the KF are dynamically changed based on the results of player detection or line detection in the video frames. The algorithm is tried on respective case study for the better result.

References

• Hitesh A Patel1, Darshak G Thakore2, "Moving Object Tracking Using Kalman Filter", IJCSMC, Vol. 2, Issue. 4, April 2013, pg. 326 – 332.
• Vibhutesh Singh, " Motion tracking/detection in Matlab using Kalman Filter", "http://www. divilabs. com/2013/11/motion-trackingdetection-in-matlab. html#ixzz30aEoYtLx"
• Jinzi Mao," Tracking a tennis ball using image processing technique", Thesis, Computer science, University of Saskatchewan,Saskatoon.
• Mukesh A. Zaveri S. N. Merchant Uday B. Desai," Small and fast moving object detection and tracking in Sports Video Sequences", 0-7803-8603-5/04/$20. 00 ©2004 IEEE.
• M. Archana1 and M. Kalaiselvi Geetha Robust Player Tracking in Broadcast Tennis Video using Kalman Filter", I J C T A, 9(2) 2016, pp. 411-418 © International Science Press.
• M. Archanaa, M. Kalaisevi Geetha, "Object Detection and Tracking based on Trajectory in Broadcast Tennis Video", ELSEVIER Procedia Computer Science 58 ( 2015 ) 225 – 232.
• Jacob Foytika, Praveen Sankaranb, Vijayan Asari, " Tracking and Recognizing Multiple Faces Using Kalman Filter and ModularPCA", ELSEVIER Procedia Computer Science 6 (2011) 256–261.
• Bodhisattwa Chakraborty, Sukadev Meher," A Trajectory-Based Ball Detection and Tracking System with Applications to Shot-type Identificationin Volleyball Videos", Dept. of Electronics and Communication Engg. National Institute of Technology Rourkela Odisha, 769008, India Email: sukadevmeher@gmail. com.
• Thota Vinod Raja, M. Tirupathamma, " Object Detection and Tracking in video using Kalman Filter", IJRAET, Volume 5, Issue 5 OCT 2016.
• Iman Iraei, Karim Faez, " Object Tracking with Occlusion Handling Using Mean Shift, Kalman Filter and Edge Histogram", Dept. Electrical Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran – Iran 2012, E-mail: iman. iraei@aut. ac. ir, kfaez@aut. ac. ir.
• C. V. Sakthi Priya1," Integrated Hidden Markov Model and Kalman Filter for Online Object Tracking", IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 6, 2013 | ISSN (online): 2321-0613.
• Nikita Rawat, Rohit Raja, "Moving Vehicle Detection and Tracking Using Modified Mean Shift Method and Kalman Filter and Research", International Journal of New Technology and Research (IJNTR) ISSN:2454-4116, Volume-2, Issue-5, May 2016 Pages 96-100.
• Qiang Huang_, Stephen Cox_, Xiangzeng Zhou, Lei Xie, "Detection of Ball Hits in a Tennis Game Using Audio and Visual Information", University of East Anglia, Norwich, UK lxie@nwpu. edu. cn , xzzhou@nwpu-aslp. org Northwestern Polytechnical University, Xi'an, China.
• Dr. Aziz Makandar, Daneshwari Mulimani," Key frame extraction and Object Detection in the Sports Video", International Conference on Soft Computing Techniques in Engineering and Technology (ASCTET) IET-2016.
• Xinguo Yu , Dirk Farin , "Current and Emerging Topics in Sports Video Processing", 0-7803-9332-5/05/$20. 00 ©2005 IEEE.

Index Terms

Keywords