Ren, R. and Jose, J.M. (2005) Football video segmentation based on video production strategy. Lecture Notes in Computer Science, 3408, pp. 433-446. (doi: 10.1007/b107096)
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football_video_segmentation.pdf 1MB |
Publisher's URL: http://dx.doi.org/10.1007/b107096
Abstract
We present a statistical approach for parsing football video structures. Based on video production conventions, a new generic structure called attack is identified, which is an equivalent of scene in other video domains. We define four video segments to construct it, namely play, focus, replay and break. Two middle level visual features, play field ratio and zoom size, are also computed. The detection process includes a two-pass classifier, a combination of Gaussian Mixture Model and Hidden Markov Models. A general suffix tree is introduced to identify and organize attack. In experiments, video structure classification accuracy of about 86% is achieved on broadcasting World Cup 2002 video data.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Jose, Professor Joemon and Ren, Dr Reede |
Authors: | Ren, R., and Jose, J.M. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
College/School: | College of Science and Engineering > School of Computing Science |
Journal Name: | Lecture Notes in Computer Science |
Publisher: | Springer |
ISSN: | 0302-9743 |
Copyright Holders: | Copyright © 2005 Springer |
First Published: | First published in Lecture Notes in Computer Science 3408:433-446 |
Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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