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Combined Dictionary Learning in Facial Expression Recognition
Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada.
Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada.
- 1 Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada.
- 2 Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada.
Journal of Signal and Information Processing·Volume 04 (2013)·Pages 86–90·Published 1 August 2013·DOI10.4236/jsip.2013.43B015
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Abstract
Dictionary learning has been applied to face recognition and gets good results. However few works applied dictionary learning in facial expression recognition. This paper investigates the application of K-SVD in facial expression recognition. Since K-SVD focuses on reconstruction and lacks discriminant capability. It has similar classification performance with image pixel values. To address this problem, this paper proposes a Combined Dictionary Scheme, which uses combination of separate dictionaries. This yields better performance than the original single dictionary scheme in terms of both recognition rate and computation complexity.
KeywordsFacial expression RecognitionDictionary LearningK-SVD
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