ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Visual Understanding with RGB-D Sensors: Volume 6 Issue 2, May 2015
Citation Count: 3
Downloads (6 Weeks): 6, Downloads (12 Months): 108, Downloads (Overall): 337
Full text available:
Human action recognition is a very active research topic in computer vision and pattern recognition. Recently, it has shown a great potential for human action recognition using the three-dimensional (3D) depth data captured by the emerging RGB-D sensors. Several features and/or algorithms have been proposed for depth-based action recognition. A ...
decision level, skeleton, spatiotemporal features, feature selection, 4D descriptor, RGB-D sensor, action recognition, depth maps, feature level, data fusion
Journal of Visual Communication and Image Representation: Volume 26 Issue C, January 2015
Publisher: Academic Press, Inc.
A new framework called TriViews is proposed for action recognition.Five different features are investigated under the TriViews framework.Two features among the five are new to depth-based action recognition.Our approach performs better than the state-of-the-art on three databases. We present an effective framework to utilize 3D depth data for action recognition, ...
3D depth data, Fusion, Public databases, PFA, Action recognition, RGB-D sensor, Kinect, TriViews framework
CVPRW '13: Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
Publisher: IEEE Computer Society
We present a novel approach to 3D human action recognition based on a feature-level fusion of spatiotemporal features and skeleton joints. First, 3D interest points detection and local feature description are performed to extract spatiotemporal motion information. Then the frame difference and pairwise distances of skeleton joint positions are computed ...
Human action recognition, 3D action recognition, fusion