NDLI: Fusion of Skeletal and Silhouette-Based Features for Human Action Recognition with RGB-D Devices

Content Provider	IEEE Xplore Digital Library
Author	Chaaraoui, A.A. Padilla-Lopez, J.R. Florez-Revuelta, F.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Technol., Univ. of Alicante, Alicante, Spain (Chaaraoui, A.A.; Padilla-Lopez, J.R.) \|\| Fac. of Sci., Eng. & Comput., Kingston Univ., Kingston upon Thames, UK (Florez-Revuelta, F.)
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.
Starting Page	91
Ending Page	97
File Size	421577
Page Count	7
File Format	PDF
ISBN	9781479930227
DOI	10.1109/ICCVW.2013.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-02
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three-dimensional displays Shape Estimation Feature extraction Real-time systems Joints
Content Type	Text
Resource Type	Article

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