Semantic shot classification in sports video

Ling-Yu Duan; Min Xu; Qi Tian

doi:10.1117/12.476259

10 January 2003 Semantic Shot Classification in Sports Video

Ling-Yu Duan, Min Xu, Qi Tian

Proceedings Volume 5021, Storage and Retrieval for Media Databases 2003; (2003) https://doi.org/10.1117/12.476259
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

In this paper, we present a unified framework for semantic shot classification in sports videos. Unlike previous approaches, which focus on clustering by aggregating shots with similar low-level features, the proposed scheme makes use of domain knowledge of a specific sport to perform a top-down video shot classification, including identification of video shot classes for each sport, and supervised learning and classification of the given sports video with low-level and middle-level features extracted from the sports video. It is observed that for each sport we can predefine a small number of semantic shot classes, about 5~10, which covers 90~95% of sports broadcasting video. With the supervised learning method, we can map the low-level features to middle-level semantic video shot attributes such as dominant object motion (a player), camera motion patterns, and court shape, etc. On the basis of the appropriate fusion of those middle-level shot classes, we classify video shots into the predefined video shot classes, each of which has a clear semantic meaning. The proposed method has been tested over 4 types of sports videos: tennis, basketball, volleyball and soccer. Good classification accuracy of 85~95% has been achieved. With correctly classified sports video shots, further structural and temporal analysis, such as event detection, video skimming, table of content, etc, will be greatly facilitated.

Citation Download Citation

Ling-Yu Duan, Min Xu, and Qi Tian "Semantic Shot Classification in Sports Video", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); https://doi.org/10.1117/12.476259

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