Real-time Expression Recognition from Dynamic Sequences of 3D Facial Scans

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dc.contributor.authorBerretti, Stefanoen_US
dc.contributor.authorBimbo, Alberto delen_US
dc.contributor.authorPala, Pietroen_US
dc.contributor.editorM. Spagnuolo and M. Bronstein and A. Bronstein and A. Ferreiraen_US
dc.date.accessioned2013-09-24T10:53:08Z
dc.date.available2013-09-24T10:53:08Z
dc.date.issued2012en_US
dc.description.abstractIn this paper, we address the problem of person-independent facial expression recognition in dynamic sequences of 3D face scans. To this end, an original approach is proposed that relies on automatically extracting a set of 3D facial points, and modeling their mutual distances along time. Training an Hidden Markov Model for every prototypical facial expression to be recognized, and combining them to form a multi-class classifier, an average recognition rate of 76.3% on the angry, happy and surprise expressions of the BU-4DFE database has been obtained. Comparison with competitor approaches on the same database shows that our solution is able to obtain effective results with the clear advantage of an implementation that fits to real-time constraints.en_US
dc.description.sectionheadersSession 3en_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-36-1en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR12/085-092en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.8 [Computer Graphics]: Applications- I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Curve, surface, solid, and object representationsen_US
dc.titleReal-time Expression Recognition from Dynamic Sequences of 3D Facial Scansen_US
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