Ball detection from broadcast soccer videos using static and dynamic features

  • Authors:

  • V. Pallavi;Jayanta Mukherjee;Arun K. Majumdar;Shamik Sural

  • Affiliations:

  • Department of Computer Science and Engineering, Indian Institute of Technology, Near IIT Gate No. 5, West Bengal, Kharagpur 721302, India;Department of Computer Science and Engineering, Indian Institute of Technology, Near IIT Gate No. 5, West Bengal, Kharagpur 721302, India;Department of Computer Science and Engineering, Indian Institute of Technology, Near IIT Gate No. 5, West Bengal, Kharagpur 721302, India;School of Information Technology, Indian Institute of Technology, Kharagpur 721302, India

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2008

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Abstract

In this paper, we propose an approach for detecting ball in broadcast soccer videos. We use hybrid techniques for identifying ball in medium and long shots. Candidate ball positions are first extracted using features based on shape and size. For medium shots, a ball is identified by filtering the candidates with the help of motion information. In long shots, after motion based filtering of the non-ball candidates, a directed weighted graph is constructed for the remaining ball candidates. Each node in the graph represents a candidate and each edge links candidates in a frame with the candidates in next two consecutive frames. Finally, dynamic programming is applied to find the longest path of the graph, which gives the actual ball trajectory. Experiments with several soccer sequences show that the proposed approach is very efficient.