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.
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.
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|Item Type:||Journal Article|
|Keywords:||Facial expression recognition, Gabor filter, (2D)2PCA, KNN|
|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:||04 Jan 2010 21:50|
|Last Modified:||29 Feb 2012 14:09|
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