Show simple item record

dc.contributor.authorZhang, Ligang
dc.contributor.authorTjondronegoro, Dian
dc.contributor.authorChandran, Vinod
dc.date.accessioned2020-01-14T05:56:31Z
dc.date.available2020-01-14T05:56:31Z
dc.date.issued2014
dc.identifier.issn0925-2312
dc.identifier.doi10.1016/j.neucom.2014.05.008
dc.identifier.urihttp://hdl.handle.net/10072/390252
dc.description.abstractRobust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of texture features in local facial regions and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. Results on the parameter sensitivity experiments demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusion ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofpagefrom451
dc.relation.ispartofpageto464
dc.relation.ispartofjournalNeurocomputing
dc.relation.ispartofvolume145
dc.subject.fieldofresearchInformation and Computing Sciences
dc.subject.fieldofresearchEngineering
dc.subject.fieldofresearchPsychology and Cognitive Sciences
dc.subject.fieldofresearchcode08
dc.subject.fieldofresearchcode09
dc.subject.fieldofresearchcode17
dc.subject.keywordsScience & Technology
dc.subject.keywordsComputer Science, Artificial Intelligence
dc.subject.keywordsComputer Science
dc.subject.keywordsFacial expression recognition
dc.titleRandom Gabor based templates for facial expression recognition in images with facial occlusion
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationZhang, L; Tjondronegoro, D; Chandran, V, Random Gabor based templates for facial expression recognition in images with facial occlusion, Neurocomputing, 2014, 145, pp. 451-464
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated2020-01-14T05:53:54Z
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2014 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorTjondronegoro, Dian W.


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record