Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84786
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dc.contributor.authorTsai, Flora S.en
dc.date.accessioned2013-07-10T06:14:05Zen
dc.date.accessioned2019-12-06T15:51:09Z-
dc.date.available2013-07-10T06:14:05Zen
dc.date.available2019-12-06T15:51:09Z-
dc.date.copyright2011en
dc.date.issued2011en
dc.identifier.urihttps://hdl.handle.net/10356/84786-
dc.identifier.urihttp://hdl.handle.net/10220/11106en
dc.description.abstractThis paper describes the usage of dimensionality reduction techniques for computer facial animation. Techniques such as Principal Components Analysis (PCA), Expectation–Maximization (EM) algorithm for PCA, Multidimensional Scaling (MDS), and Locally Linear Embedding (LLE) are compared for the purpose of facial animation of different emotions. The experimental results on our facial animation data demonstrate the usefulness of dimensionality reduction techniques for both space and time reduction. In particular, the EMPCA algorithm performed especially well in our dataset, with negligible error of only 1–2%.en
dc.language.isoenen
dc.relation.ispartofseriesExpert systems with applicationsen
dc.rights© 2011 Elsevier Ltd.en
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen
dc.titleDimensionality reduction for computer facial animationen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.identifier.doihttp://dx.doi.org/10.1016/j.eswa.2011.10.018en
item.grantfulltextnone-
item.fulltextNo Fulltext-
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