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Detecting pitching frames in baseball game video using Markov random walk

11 years 3 months ago
Detecting pitching frames in baseball game video using Markov random walk
Pitching is the starting point of an event in baseball games. Hence, locating pitching shots is a critical step in content analysis of a baseball game video. However, pitching frames vary with innings and games. Existing methods that require a great deal of effort to construct empirical rules or label training data do not capture the characteristics of various pitching frames very well. In this paper, we present an unsupervised method for pitching frame detection by using Markov random walk. A video stream is first divided into content-homogeneous shots, and these shots are merged into states through hierarchical agglomerative clustering. Then, the state with the highest visit probability according to the Markov random walk theory is deemed the set of pitching frames. Finally, a model trained on the pitching frames in the pitching state is further used to detect the remaining potential pitching frames in other states. Our experiments demonstrate that the proposed method yields satisfa...
Chih-Yi Chiu, Po-Chih Lin, Wei-Ming Chang, Hsin-Mi
Added 12 Feb 2011
Updated 12 Feb 2011
Type Journal
Year 2010
Where ICIP
Authors Chih-Yi Chiu, Po-Chih Lin, Wei-Ming Chang, Hsin-Min Wang, Shi-Nine Yang
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