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3D Point Cloud Based Hybrid Maps Reconstruction for Indoor Environments Read chapter Read first chapter

2013 | OriginalPaper | Chapter

2. Efficient Discriminative K-SVD for Facial Expression Recognition

Authors : Weifeng Liu, Caifeng Song, Yanjiang Wang

Published in: Proceedings of 2013 Chinese Intelligent Automation Conference

Publisher: Springer Berlin Heidelberg

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Abstract

Dictionary learning has attracted growing intention for its prominent performance in many computer vision applications including facial expression recognition (FER). Discriminative K-SVD (D-KSVD) is one of conventional dictionary learning methods, which can effectively unify dictionary learning and classifier. However, the computation is huge when applying D-KSVD directly on Gabor features which has high dimension. To tackle this problem, we employ random projection on Gabor features and then put the reduced features into D-KSVD schema to obtain sparse representation and dictionary. To evaluate the performance, we implement the proposed method for FER on JAFFE database. We also employ support vector machine (SVM) on the sparse codes for FER. Experimental results show that the computation is reduced a lot with little performance lost.

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Metadata
Title
Efficient Discriminative K-SVD for Facial Expression Recognition
Authors
Weifeng Liu
Caifeng Song
Yanjiang Wang
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Proceedings of 2013 Chinese Intelligent Automation Conference

Print ISBN: 978-3-642-38465-3

Electronic ISBN: 978-3-642-38466-0

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-38466-0_2