Extracting Story Units in Sports Video Based on Unsupervised Video Scene Clustering

Author

Liu, Chunxi ; Huang, Qingming ; Jiang, Shuqiang ; Zhang, Weigang

Author_Institution

Graduate Univ. of Chinese Acad. of Sci., Beijing

fYear

2006

fDate

9-12 July 2006

Firstpage

1605

Lastpage

1608

Abstract

Many sports videos such as archery, diving and tennis have repetitive structure patterns. They are reliable clues to generate highlights, summarization and automatic annotation. In this paper, we present a novel approach to analyze these structure patterns in sports video to extract story units. First, an unsupervised scene clustering method for sports video is adopted to automatically categorize the video shots into several disparate scenes. Then, the clustering results are modeled by a transition matrix. Finally, the key scene shots are detected to analyze the structure patterns and extract the story units. Experimental results on several types of broadcast sports video demonstrate that our approach is effective

Keywords

feature extraction; pattern clustering; sport; video signal processing; sports video broadcast; story unit extraction; structure pattern analysis; transition matrix; unsupervised video scene clustering; Clustering methods; Computers; Data mining; Games; Gunshot detection systems; Hidden Markov models; Layout; Multimedia communication; Pattern analysis; Water storage;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia and Expo, 2006 IEEE International Conference on

Conference_Location

Toronto, Ont.

Print_ISBN

1-4244-0366-7

Electronic_ISBN

1-4244-0367-7

Type

conf

DOI

10.1109/ICME.2006.262853

Filename

4036922