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

Roh, MC, Christmas, W, Kittler, J and Lee, SW (2006) Robust player gesture spotting and recognition in low-resolution sports video

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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. © Springer-Verlag Berlin Heidelberg 2006.

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Divisions :	Surrey research (other units)
Authors :	Name Email ORCID Roh, MC Christmas, W w.christmas@surrey.ac.uk Kittler, J j.kittler@surrey.ac.uk Lee, SW
Date :	17 July 2006
DOI :	10.1007/11744085_27
Depositing User :	Symplectic Elements
Date Deposited :	17 May 2017 11:29
Last Modified :	23 Jan 2020 16:54
URI:	http://epubs.surrey.ac.uk/id/eprint/831544

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