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2008

Gesture spotting for low-resolution sports video annotation

13 years 2 months ago
Gesture spotting for low-resolution sports video annotation
Human gesture recognition plays an important role in automating the analysis of video material at a high level. Especially in sports videos, the determination of the player's gestures is a key task. In many sports views, the camera covers a large part of the sports arena, resulting in low resolution of the player's region. Moreover, the camera is not static, but moves dynamically around its optical center, i.e. pan/tilt/zoom camera. These factors make the determination of the player's gestures a challenging task. To overcome these problems, we propose a posture descriptor that is robust to shape corruption of the player's silhouette, and a gesture spotting method that is robust to noisy sequences of data and needs only a small amount of training data. The proposed posture descriptor extracts the feature points of a shape, based on the curvature scale space (CSS) method. The use of CSS makes this method robust to local noise, and our method is also robust to signifi...
Myung-Cheol Roh, William J. Christmas, Josef Kittl
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where PR
Authors Myung-Cheol Roh, William J. Christmas, Josef Kittler, Seong-Whan Lee
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