Fusion of Skeletal and Silhouette-based Features for Human Action Recognition with RGB-D Devices

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/34417
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Title: Fusion of Skeletal and Silhouette-based Features for Human Action Recognition with RGB-D Devices
Authors: Chaaraoui, Alexandros Andre | Padilla López, José Ramón | 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 | RGB-D | Kinect | Fusion | Silhouette | Skeleton
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: Dec-2013
Publisher: IEEE
Abstract: Since the Microsoft Kinect has been released, the usage of marker-less body pose estimation has been enormously eased. Based on 3D skeletal pose information, complex human gestures and actions can be recognised in real time. However, due to errors in tracking or occlusions, the obtained information can be noisy. Since the RGB-D data is available, the 3D or 2D shape of the person can be used instead. However, depending on the viewpoint and the action to recognise, it might present a low discriminative value. In this paper, the combination of body pose estimation and 2D shape, in order to provide additional characteristic value, is considered so as to improve human action recognition. Using efficient feature extraction techniques, skeletal and silhouette-based features are obtained which are low dimensional and can be obtained in real time. These two features are then combined by means of feature fusion. The proposed approach is validated using a state-of-the-art learning method and the MSR Action3D dataset as benchmark. The obtained results show that the fused feature achieves to improve the recognition rates, outperforming state-of-the-art results in recognition rate and robustness.
Description: Paper submitted to CDC4CV, 3rd IEEE Workshop on Consumer Depth Cameras for Computer Vision, in conjunction with ICCV 2013, Dec. 2, Sydney, Australia.
Sponsor: This work has been partially supported 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) and 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). Alexandros Andre Chaaraoui and José Ramón Padilla-López acknowledge financial support by the Conselleria d’Educació, Formació i Ocupació of the Generalitat Valenciana (fellowships ACIF/2011/160 and ACIF/2012/064 respectively).
URI: http://hdl.handle.net/10045/34417
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Peer Review: si
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