International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.9, No.1, Jan. 2017

Subspace based Expression Recognition Using Combinational Gabor based Feature Fusion

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G. P. Hegde, M. Seetha

Index Terms

Discriminant analysis;Gabor filter;Expression recognition;Feature extraction; Subspace;Geometrical feature


This paper demonstrates mainly on enhancement of extracted feature and proposes a novel approach for feature level fusion for efficient expression recognition. Extracted Gabor filter magnitude feature vector has been fused with upper face part geometrical features and Gabor phase feature vector has been fused with lower face part geometrical features respectively. Both these high dimensional feature dataset have been projected into low dimensional subspace for de-correlating the feature data redundancy by preserving local and global discriminative features of various expression classes of JAFFE, YALE and FD databases. The effectiveness of subspace of fused dataset has been measured with different dimensional parameters of Gabor filter. The experimental results reveal that performance of the subspace approaches for high dimensional proposed feature level fused dataset yields higher accuracy rates compared to state of art approaches. 

Cite This Paper

G. P. Hegde, M. Seetha,"Subspace based Expression Recognition Using Combinational Gabor based Feature Fusion", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.9, No.1, pp.50-60, 2017.DOI: 10.5815/ijigsp.2017.01.07


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