Facial Expression Recognition Based on Monogenic Binary Coding

Xiao Xiao Xia; Zi Lu Ying; Wen Jin Chu

doi:10.4028/www.scientific.net/AMM.511-512.437

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 511-512Facial Expression Recognition Based on Monogenic...

Facial Expression Recognition Based on Monogenic Binary Coding

Abstract:

A new method based on Monogenic Binary Coding (MBC) is proposed for facial expression feature extraction and representation. Firstly, monogenic signal analysis is used to extract multi-scale magnitude, orientation and phase components. Secondly, Monogenic Binary Coding (MBC) is used to encode the monogenic local variation and intensity in local regions of each extracted component in each scale and local histograms are built. Then Blocked Fisher Linear Discrimination (BFLD) is used to reduce the dimensionality of histogram features and to enhance discrimination. Finally the three complementary components are fused for more effective facial expression recognition (FER). Experiment results on Japanese female expression database (JAFFE) show that the performance of the fusion method is even better than state-of-the-art local feature based FER methods such as Local Binary Pattern (LBP)+Sparse Representation (SRC), Local Phase Quantization (LPQ)+SRC ,etc.

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Periodical:

Applied Mechanics and Materials (Volumes 511-512)

Pages:

437-440

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.511-512.437

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Cite this paper

Online since:

February 2014

Authors:

Xiao Xiao Xia, Zi Lu Ying*, Wen Jin Chu

Keywords:

BFLD, Facial Expression Recognition (FER), Monogenic Binary Coding (MBC)

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* - Corresponding Author

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