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Summary
In this project, we investigate
the problem of parsing the structure of broadcast soccer programs using
statistical techniques, especially Hidden Markov models. The problem is
important for applications such as personalized video streaming and browsing
systems, in which video are segmented into different states and important
states are selected based on user preferences. While prior work focuses
on the detection of special events such as goals or corner kicks, this
work is concerned with generic structural elements of the game. We define
two mutually exclusive states of the game, play and break based on the
rules of soccer. Automatic detection of such generic states represents
an original, challenging issue due to high appearance diversities and
temporal dynamics of such states in different videos. We select a salient
feature set from the compressed domain, dominant color ratio and motion
intensity, based on the special syntax and content characteristics of
soccer videos. We then model the stochastic structures of each state of
the game with a set of hidden Markov models. Finally, higher-level transitions
are taken into account and dynamic programming techniques are used to
obtain the maximum likelihood segmentation of the video sequence. The
system achieves a promising classification accuracy of 83.5%, with light-weight
computation on feature extraction and model inference, as well as a satisfactory
accuracy in boundary timing.
People
Lexing
Xie, Peng
Xu
Prof. Shih-Fu Chang
Publication
L. Xie, P. Xu, S.-F. Chang,
A. Divakaran and H. Sun, Structure
Analysis of Soccer Video with Domain Knowledge and Hidden Markov Models,
Pattern Recognition Letters, to appear. (PS.GZ/PDF)
L. Xie, S.-F. Chang, A. Divakaran
and H. Sun, Structure
Analysis of Soccer Video with Hidden Markov Models, Proc. Interational
Conference on Acoustic, Speech and Signal Processing, (ICASSP-2002), Orlando,
FL, USA, May 13-17, 2002.
(PS.GZ/
PDF)
P. Xu, L. Xie, S.-F. Chang,
A. Divakaran, A. Vetro, H. Sun, Algorithms
and Systems for Segmentation and Structure Analysis in Soccer Video,
IEEE International Conference on Multimedia and Expo, Tokyo, Japan, Aug.
22-25, 2001. (PS.GZ/PDF)
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Last updated: September 27, 2003.
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