Evaluation of spatiotemporal detectors and descriptors for facial expression recognition

Mohammed Bennamoun, Munawar Hayat, Senjian An

Research output: A Conference proceeding or a Chapter in BookConference contribution

9 Citations (Scopus)

Abstract

Local spatiotemporal detectors and descriptors have recently become very popular for video analysis in many applications. They do not require any preprocessing steps and are invariant to spatial and temporal scales. Despite their computational simplicity, they have not been evaluated and tested for video analysis of facial data. This paper considers two space-time detectors and four descriptors and uses bag of features framework for human facial expression recognition on BU_4DFE data set. A comparison of local spatiotemporal features with other non-spatiotemporal published techniques on the same data set is also given. Unlike spatiotemporal features, these techniques involve time consuming and computationally intensive preprocessing steps like manual initialization and tracking of facial points. Our results show that despite being totally automatic and not requiring any user intervention, local spacetime features provide promising and comparable performance for facial expression recognition on BU_4DFE data set
Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Human System Interactions, HSI 2012
Place of PublicationPerth, WA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages43-47
Number of pages5
ISBN (Electronic)9780769548944
ISBN (Print)9780769548944
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 5th international conference on Human system interactions (HSI) - Perth, Perth, Australia
Duration: 6 Jun 20148 Jun 2014

Publication series

NameInternational Conference on Human System Interaction, HSI

Conference

Conference2012 5th international conference on Human system interactions (HSI)
CountryAustralia
CityPerth
Period6/06/148/06/14

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