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Automatic skin segmentation for gesture recognition combining region and support vector machine active learning

Han, Junwei and Awad, George M. and Sutherland, Alistair and Wu, Hai (2006) Automatic skin segmentation for gesture recognition combining region and support vector machine active learning. In: FGR 2006 - The 7th International Conference on Automatic Face and Gesture Recognition, 10-12 April 2006, Southampton, UK.

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Abstract

Skin segmentation is the cornerstone of many applications such as gesture recognition, face detection, and objectionable image filtering. In this paper, we attempt to address the skin segmentation problem for gesture recognition. Initially, given a gesture video sequence, a generic skin model is applied to the first couple of frames to automatically collect the training data. Then, an SVM classifier based on active learning is used to identify the skin pixels. Finally, the results are improved by incorporating region segmentation. The proposed algorithm is fully automatic and adaptive to different signers. We have tested our approach on the ECHO database. Comparing with other existing algorithms, our method could achieve better performance.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Information retrieval
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/FGR.2006.27
Copyright Information:Copyright © 2006 IEEE. Reprinted from FGR 2006 - The 7th International Conference on Automatic Face and Gesture Recognition. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Dublin City University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Funders:Science Foundation Ireland, SFI 03/IN.3/I361
ID Code:233
Deposited On:05 Mar 2008 by DORAS Administrator. Last Modified 05 May 2010 14:19

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