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Robust player gesture spotting and recognition in low-resolution sports video

Authors
Roh, Myung-CheolChristmas, BillKittler, JosephLee, Seong-Whan
Issue Date
2006
Publisher
SPRINGER-VERLAG BERLIN
Citation
COMPUTER VISION - ECCV 2006, PT 4, PROCEEDINGS, v.3954, pp.347 - 358
Indexed
SCIE
SCOPUS
Journal Title
COMPUTER VISION - ECCV 2006, PT 4, PROCEEDINGS
Volume
3954
Start Page
347
End Page
358
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/123194
ISSN
0302-9743
Abstract
The determination of the player's gestures and actions in sports video is a key task in automating the analysis of the video material at a high level. In many sports views, the camera covers a large part of the sports arena, so that the resolution of player's region is low. This makes the determination of the player's gestures and actions a challenging task, especially if there is large camera motion. To overcome these problems, we propose a method based on curvature scale space templates of the player's silhouette. The use of curvature scale space makes the method robust to noise and our method is robust to significant shape corruption of a part of player's silhouette. We also propose a new recognition method which is robust to noisy sequences of data and needs only a small amount of training data.
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