TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Human action recognition in stereoscopic videos based on bag of features and disparity pyramids

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoEuropean Signal Processing Conference
KustantajaEuropean Signal Processing Conference, EUSIPCO
Sivut1317-1321
Sivumäärä5
ISBN (painettu)9780992862619
TilaJulkaistu - 10 marraskuuta 2014
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
Tapahtuma22nd European Signal Processing Conference, EUSIPCO 2014 - Lisbon, Portugali
Kesto: 1 syyskuuta 20145 syyskuuta 2014

Conference

Conference22nd European Signal Processing Conference, EUSIPCO 2014
MaaPortugali
KaupunkiLisbon
Ajanjakso1/09/145/09/14

Tiivistelmä

In this paper, we propose a method for human action recognition in unconstrained environments based on stereoscopic videos. We describe a video representation scheme that exploits the enriched visual and disparity information that is available for such data. Each stereoscopic video is represented by multiple vectors, evaluated on video locations corresponding to different disparity zones. By using these vectors, multiple action descriptions can be determined that either correspond to specific disparity zones, or combine information appearing in different disparity zones in the classification phase. Experimental results denote that the proposed approach enhances action classification performance, when compared to the standard approach, and achieves state-of-the-art performance on the Hollywood 3D database designed for the recognition of complex actions in unconstrained environments.

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