Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2010.919
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dc.titleResampling approach to facial expression recognition using 3D meshes
dc.contributor.authorVenkatesh, Y.V.
dc.contributor.authorKassim, A.K.
dc.contributor.authorMurthy, O.V.R.
dc.date.accessioned2014-06-19T03:25:48Z
dc.date.available2014-06-19T03:25:48Z
dc.date.issued2010
dc.identifier.citationVenkatesh, Y.V.,Kassim, A.K.,Murthy, O.V.R. (2010). Resampling approach to facial expression recognition using 3D meshes. Proceedings - International Conference on Pattern Recognition : 3772-3775. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICPR.2010.919" target="_blank">https://doi.org/10.1109/ICPR.2010.919</a>
dc.identifier.isbn9780769541099
dc.identifier.issn10514651
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/71618
dc.description.abstractWe propose a novel strategy, based on resampling of 3D meshes, to recognize facial expressions. This entails conversion of the existing irregular 3D mesh structure in the database to a uniformly sampled 3D matrix structure. An important consequence of this operation is that the classical correspondence problem can be dispensed with. In the present paper, in order to demonstrate the feasibility of the proposed strategy, we employ only spectral flow matrices as features to recognize facial expressions. Experimental results are presented, along with suggestions for possible refinements to the strategy to improve classification accuracy. © 2010 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICPR.2010.919
dc.sourceScopus
dc.subject3D meshes
dc.subjectFacial expression recognition
dc.subjectFourier transform
dc.subjectK-means clustering
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/ICPR.2010.919
dc.description.sourcetitleProceedings - International Conference on Pattern Recognition
dc.description.page3772-3775
dc.description.codenPICRE
dc.identifier.isiutNOT_IN_WOS
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