By Topic

Research on Event Detection of Soccer Video Based on Hidden Markov Model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Zhao Pixi ; Comput. Sch., Dalian Nat. Univ., Dalian, China ; Li Hongyan ; Wang Wei

For soccer video, the algorithm that using semantic shots as observation, the events as the states to construct the Hidden Markov Model (HMM) for event detection was proposed. The nine types of semantic shots such as front region, midfield, penalty area, the medium shot, the players close-up, outside audience, referee shot, slow motion playback shot and other types are used as observation. The four kinds of events to be detected, namely, the normal playing event, play suspension event, shooting event and foul event are defined as the states. According to the decoding principle of HMM, the states sequence with the maximum possibility for the input observation sequence was calculated and thus the event detection was completed. Compared with other event detection algorithms based on HMM assessment principle, the method adopted in this paper only has to construct one HMM and need less computation time. The experiment results show that our algorithm is effective.

Published in:

Computational and Information Sciences (ICCIS), 2010 International Conference on

Date of Conference:

17-19 Dec. 2010