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A Novel Intelligent Multiple Watermarking Schemes for the Protection of the Information Content of a Document Image Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Dictionary Based Approach for Facial Expression Recognition from Static Images

Authors : Krishan Sharma, Renu Rameshan

Published in: Computer Vision, Graphics, and Image Processing

Publisher: Springer International Publishing

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Abstract

We present a simple approach for facial expression recognition from images using the principle of sparse representation using a learned dictionary. Visual appearance based feature descriptors like histogram of oriented gradients (HOG), local binary patterns (LBP) and eigenfaces are used. We use Fisher discrimination dictionary which has discrimination capability in addition to being reconstructive. The classification is based on the fact that each expression class with in the dictionary spans a subspace and these subspaces have non-overlapping directions so that they are widely separated. Each test feature point has a sparse representation in the union of subspaces of dictionary formed by labeled training points. To check recognition performance of the proposed approach, extensive experimentation is done over Jaffee and CK databases. Results show that the proposed approach has better classification accuracy than state-of-the-art techniques.

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previous chapter Photometric Normalization Techniques for Extended Multi-spectral Face Recognition: A Comparative Analysis
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Metadata
Title
Dictionary Based Approach for Facial Expression Recognition from Static Images
Authors
Krishan Sharma
Renu Rameshan
Copyright Year
2017
Book
Computer Vision, Graphics, and Image Processing

Print ISBN: 978-3-319-68123-8

Electronic ISBN: 978-3-319-68124-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-68124-5_4

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