DocumentCode :
3467078
Title :
Fusion of Skeletal and Silhouette-Based Features for Human Action Recognition with RGB-D Devices
Author :
Chaaraoui, Alexandros Andre ; Padilla-Lopez, Jose Ramon ; Florez-Revuelta, Francisco
Author_Institution :
Dept. of Comput. Technol., Univ. of Alicante, Alicante, Spain
fYear :
2013
fDate :
2-8 Dec. 2013
Firstpage :
91
Lastpage :
97
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.
Keywords :
feature extraction; image colour analysis; image fusion; image sensors; learning (artificial intelligence); pose estimation; 2D shape; 3D skeletal pose information; MSR Action3D dataset; Microsoft Kinect; RGB-D devices; characteristic value; feature extraction techniques; feature fusion; human action recognition; human gestures; learning method; marker-less body pose estimation; recognition rates; red-green-blue-depth device; silhouette-based features; skeletal features; viewpoint; Estimation; Feature extraction; Joints; Real-time systems; Shape; Three-dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/ICCVW.2013.19
Filename :
6755884
Link To Document :
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