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Proceedings Paper

Mutual information-based facial expression recognition
Author(s): Mliki Hazar; Mohamed Hammami; Ben-Abdallah Hanêne
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Paper Abstract

This paper introduces a novel low-computation discriminative regions representation for expression analysis task. The proposed approach relies on interesting studies in psychology which show that most of the descriptive and responsible regions for facial expression are located around some face parts. The contributions of this work lie in the proposition of new approach which supports automatic facial expression recognition based on automatic regions selection. The regions selection step aims to select the descriptive regions responsible or facial expression and was performed using Mutual Information (MI) technique. For facial feature extraction, we have applied Local Binary Patterns Pattern (LBP) on Gradient image to encode salient micro-patterns of facial expressions. Experimental studies have shown that using discriminative regions provide better results than using the whole face regions whilst reducing features vector dimension.

Paper Details

Date Published: 24 December 2013
PDF: 5 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90670G (24 December 2013); doi: 10.1117/12.2049866
Show Author Affiliations
Mliki Hazar, Univ. of Sfax (Tunisia)
Mohamed Hammami, Univ. of Sfax (Tunisia)
Ben-Abdallah Hanêne, Univ. of Sfax (Tunisia)
King Abdulaziz Univ. (Saudi Arabia)


Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Jianhong Zhou; Antanas Verikas, Editor(s)

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