Feature selection based on co-clustering for effective facial expression recognition

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Detail(s)

Original languageEnglish
Title of host publication2016 International Conference on Machine Learning and Cybernetics (ICMLC)
PublisherIEEE Systems, Man, and Cybernetics Society
ISBN (Electronic)978-1-5090-0390-7
ISBN (Print)978-1-5090-0391-4
Publication statusPublished - 23 Feb 2017

Publication series

Name
ISSN (Print)2160-133X

Conference

Title2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017
LocationColorado Convention Center
PlaceUnited States
CityDenver
Period6 - 11 May 2017

Abstract

Facial expressions are considered to be an effective and non-verbal means of expressing the emotional states of humans in more natural and non-intrusive way. Automatically recognizing the emotions consequently contributes towards the advances in the areas such as human computer interaction, clinical psychology and data-driven animations. Deriving a relevant and reduced set of features is a vital step for effective facial expression recognition. In this paper, we propose a co-clustering based approach to the selection of distinguished and interpretable features to deal with the curse of dimensionality issue. First, the features are extracted from images using a bank of Gabor filters. Then, a co-clustering based algorithm is designed to seek distinguishable features based on their non-inclusive information in co-clusters. Experiments illustrate that the selected features are accurate and effective for the facial expression recognition on JAFFE database and the best recognition rate is obtained by using selected features with SVM for classification. Moreover, we illustrate that the selected features not only reduces the dimensionality but also identify the distinguishable face regions on images amongst all expressions.

Research Area(s)

  • Computer Vision

Citation Format(s)

Feature selection based on co-clustering for effective facial expression recognition. / KHAN, Sheheryar; CHEN, Lijiang; ZHE, Xuefei; YAN, Hong.

2016 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE Systems, Man, and Cybernetics Society, 2017.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)