Motion entropy feature and its applications to event-based segmentation of sports video

被引：23

作者：

Chen, Chen-Yu ^{[1
]}

Wang, Jia-Ching ^{[1
]}

Wang, Jhing-Fa ^{[1
]}

Hu, Yu-Hen ^{[2
]}

机构：

[1] Natl Cheng Kung Univ, Dept Elect Engn, Tainan 701, Taiwan

[2] Univ Wisconsin, Dept Elect & Comp Engn, Madison, WI 53706 USA

来源：

EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING | 2008年 / 2008卷 / 1期

关键词：

Video Sequence; Change Point; Object Motion; Full Article; Point Detection;

D O I：

10.1155/2008/460913

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

An entropy-based criterion is proposed to characterize the pattern and intensity of object motion in a video sequence as a function of time. By applying a homoscedastic error model-based time series change point detection algorithm 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. Copyright (C) 2008 Chen-Yu Chen et al.

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