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Content Provider | IEEE Xplore Digital Library |
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Author | Chen-Yu Chen Jia-Ching Wang Jhing-Fa Wang Yu-Hen Hu |
Copyright Year | 2007 |
Description | Author affiliation: Nat. Cheng Kung Univ., Tainan (Chen-Yu Chen; Jia-Ching Wang; Jhing-Fa Wang) |
Abstract | An event-based segmentation method for sports videos is presented. A motion entropy criterion is employed to characterize the level of intensity of relevant object motion in individual frames of a video sequence. The resulting motion entropy curve then is approximated with a piece-wise linear model using a homoscedastic error model based time series change point detection algorithm. It is observed that interesting sports events are correlated with specific patterns of the piece-wise linear model. A set of empirically derived classification rules then is derived based on these observations. Application of these rules to the motion entropy curve leads to this motion entropy curve, one is able to segment the corresponding video sequence into individual sections, each consisting of a semantically relevant event. The proposed method is tested on six hours of sports videos including basketball, soccer and tennis. Excellent experimental results are observed. |
Starting Page | 107 |
Ending Page | 111 |
File Size | 300684 |
Page Count | 5 |
File Format | |
ISBN | 9780769530581 |
DOI | 10.1109/ISM.2007.4412363 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-12-10 |
Publisher Place | Taiwan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Entropy Layout Video sequences Piecewise linear techniques Motion estimation Detection algorithms Testing Computer vision Event detection Surveillance |
Content Type | Text |
Resource Type | Article |
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