Extraction and representation of human body for pitching style recognition in broadcast baseball video

  • Authors:

  • Hua-Tsung Chen; Chien-Li Chou;Wen-Jiin Tsai;Suh-Yin Lee; Jen-Yu Yu

  • Affiliations:

  • Dept. of Computer Science, National Chiao Tung University, Hsinchu, Taiwan;Dept. of Computer Science, National Chiao Tung University, Hsinchu, Taiwan;Dept. of Computer Science, National Chiao Tung University, Hsinchu, Taiwan;Dept. of Computer Science, National Chiao Tung University, Hsinchu, Taiwan;ICL/Industrial Technology Research Institute, Hsinchu, Taiwan

  • Venue:
  • ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
  • Year:
  • 2011

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Abstract

In baseball games, different release points of pitchers form several kinds of pitching styles. Different pitching styles possess individual advantages. This paper presents a novel pitching style recognition approach for automatic generation of game information and video annotation. First, an effective object segmentation algorithm is designed to compute the body contour and extract the pitcher's body. Then, star skeleton is used as the representative descriptor of the pitcher posture for pitching style recognition. The proposed approach has been tested on broadcast baseball video and the promising experimental results validate the robustness and practicability.