An efficient method for facial expression recognition

Xudong Xie; Kin Man Lam

doi:10.1117/12.631546

An efficient method for facial expression recognition

Xudong Xie, Kin Man Lam

The Hong Kong Polytechnic University

Research output: Journal article publication › Conference article › Academic research › peer-review

Abstract

In this paper, an efficient method for human facial expression recognition is presented. Our method includes two major techniques: spatially maximum occurrence model (SMOM), which is used to describe the different facial expressions; and elastic shape-texture matching (ESTM), which is used to compute the similarity between two images. The combination of these two techniques, namely the SMOM-ESTM method, is used to classify the facial expressions. With our approach, the recognition rate based on the AR database is 94.5%.

Original language	English
Pages (from-to)	786-793
Number of pages	8
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	5960
Issue number	2
DOIs	https://doi.org/10.1117/12.631546
Publication status	Published - 1 Dec 2005
Event	Visual Communications and Image Processing 2005 - Beijing, China Duration: 12 Jul 2005 → 15 Jul 2005

Keywords

Elastic shape-texture matching
Facial expression recognition
Spatially maximum occurrence model

ASJC Scopus subject areas

Electrical and Electronic Engineering
Condensed Matter Physics

More information

10.1117/12.631546

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title = "An efficient method for facial expression recognition",

abstract = "In this paper, an efficient method for human facial expression recognition is presented. Our method includes two major techniques: spatially maximum occurrence model (SMOM), which is used to describe the different facial expressions; and elastic shape-texture matching (ESTM), which is used to compute the similarity between two images. The combination of these two techniques, namely the SMOM-ESTM method, is used to classify the facial expressions. With our approach, the recognition rate based on the AR database is 94.5%.",

keywords = "Elastic shape-texture matching, Facial expression recognition, Spatially maximum occurrence model",

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AB - In this paper, an efficient method for human facial expression recognition is presented. Our method includes two major techniques: spatially maximum occurrence model (SMOM), which is used to describe the different facial expressions; and elastic shape-texture matching (ESTM), which is used to compute the similarity between two images. The combination of these two techniques, namely the SMOM-ESTM method, is used to classify the facial expressions. With our approach, the recognition rate based on the AR database is 94.5%.

KW - Elastic shape-texture matching

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KW - Spatially maximum occurrence model

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ER -

An efficient method for facial expression recognition

Abstract

Keywords

ASJC Scopus subject areas

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