Silhouette-based human action recognition using sequences of key poses

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Title: Silhouette-based human action recognition using sequences of key poses
Authors: Chaaraoui, Alexandros Andre | Climent Pérez, Pau | Flórez-Revuelta, Francisco
Research Group/s: Informática Industrial y Redes de Computadores | Domótica y Ambientes Inteligentes
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Keywords: Human action recognition | Key pose | Key pose sequence | Weizmann dataset | MuHAVi dataset | IXMAS dataset
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: 1-Nov-2013
Publisher: Elsevier
Citation: Pattern Recognition Letters. 2013, 34(15): 1799-1807. doi:10.1016/j.patrec.2013.01.021
Abstract: In this paper, a human action recognition method is presented in which pose representation is based on the contour points of the human silhouette and actions are learned by making use of sequences of multi-view key poses. Our contribution is twofold. Firstly, our approach achieves state-of-the-art success rates without compromising the speed of the recognition process and therefore showing suitability for online recognition and real-time scenarios. Secondly, dissimilarities among different actors performing the same action are handled by taking into account variations in shape (shifting the test data to the known domain of key poses) and speed (considering inconsistent time scales in the classification). Experimental results on the publicly available Weizmann, MuHAVi and IXMAS datasets return high and stable success rates, achieving, to the best of our knowledge, the best rate so far on the MuHAVi Novel Actor test.
Sponsor: This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02) and by the European Commission under project “caring4U – A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010–274649). Alexandros Andre Chaaraoui acknowledges financial support by the Conselleria d’Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2011/160).
ISSN: 0167-8655 (Print) | 1872-7344 (Online)
DOI: 10.1016/j.patrec.2013.01.021
Language: eng
Type: info:eu-repo/semantics/article
Peer Review: si
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