Gesture spotting in low-quality video with features based on curvature scale space

Myung Cheol Roh, Bill Christmas, Joseph Kittler, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Player's gesture and action spotting in sports video is a key task in automatic 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 area of player's region is small, and has large motion. These make the determination of the player's gestures and actions a challenging task. 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 sequence of posture and needs only a small amount of training data, which is essential characteristic for many practical applications.

Original languageEnglish
Title of host publicationFGR 2006: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Pages375-380
Number of pages6
Volume2006
DOIs
Publication statusPublished - 2006 Nov 14
EventFGR 2006: 7th International Conference on Automatic Face and Gesture Recognition - Southampton, United Kingdom
Duration: 2006 Apr 102006 Apr 12

Other

OtherFGR 2006: 7th International Conference on Automatic Face and Gesture Recognition
CountryUnited Kingdom
CitySouthampton
Period06/4/1006/4/12

ASJC Scopus subject areas

  • Engineering(all)

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    Roh, M. C., Christmas, B., Kittler, J., & Lee, S. W. (2006). Gesture spotting in low-quality video with features based on curvature scale space. In FGR 2006: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition (Vol. 2006, pp. 375-380). [1613049] https://doi.org/10.1109/FGR.2006.59