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Selecting, optimizing and fusing ‘salient’ Gabor features for facial expression recognition

Zhang, Ligang & Tjondronegoro, Dian W. (2009) Selecting, optimizing and fusing ‘salient’ Gabor features for facial expression recognition. Neural Information Processing (Lecture Notes in Computer Science), Part I, pp. 724-732.

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Abstract

This paper describes a novel framework for facial expression recognition from still images by selecting, optimizing and fusing ‘salient’ Gabor feature layers to recognize six universal facial expressions using the K nearest neighbor classifier. The recognition comparisons with all layer approach using JAFFE and Cohn-Kanade (CK) databases confirm that using ‘salient’ Gabor feature layers with optimized sizes can achieve better recognition performance and dramatically reduce computational time. Moreover, comparisons with the state of the art performances demonstrate the effectiveness of our approach.

Impact and interest:

2 citations in Scopus
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3 citations in Web of Science®

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Full-text downloads:

240 since deposited on 04 Jan 2010
21 in the past twelve months

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ID Code: 28618
Item Type: Journal Article
Additional URLs:
Keywords: Facial expression recognition, Gabor filter, (2D)2PCA, KNN
DOI: 10.1007/978-3-642-10677-4_83
ISBN: 3642106765
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2009 Springer-Verlag GmbH Berlin Heidelberg
Copyright Statement: The original publication is available at: http://www.springerlink.com
Deposited On: 05 Jan 2010 07:50
Last Modified: 01 Mar 2012 00:09

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