Two-Stream Temporal Convolutional Networks for Skeleton-Based Human Action Recognition-Reference-Cited by-同舟云学术

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Two-Stream Temporal Convolutional Networks for Skeleton-Based Human Action Recognition

Published:2020-05 Issue:3 Volume:35 Page:538-550
ISSN:1000-9000
Container-title:Journal of Computer Science and Technology
language:en
Short-container-title:J. Comput. Sci. Technol.

Author:

Jia Jin-Gong,Zhou Yuan-Feng,Hao Xing-Wei,Li Feng,Desrosiers Christian,Zhang Cai-Ming

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s11390-020-0405-6.pdf

Reference43 articles.

1. Aggarwal J K, Xia L. Human activity recognition from 3D data: A review. Pattern Recognition Letters, 2014, 48: 70-80.

2. Weinland D, Ronfard R, Boyer E. A survey of vision-based methods for action representation, segmentation and recognition. Computer Vision and Image Understanding, 2011, 115(2): 224-241.

3. Han F, Reily B, Hoff W, Zhang H. Space-time representation of people based on 3D skeletal data: A review. Computer Vision and Image Understanding, 2017, 158: 85-105.

4. Liu H, Liu B, Zhang H, Li L, Qin X, Zhang G. Crowd evacuation simulation approach based on navigation knowledge and two-layer control mechanism. Information Sciences, 2018, 436/437: 247-267.

5. Turaga P, Chellappa R, Subrahmanian V S. Machine recognition of human activities: A survey. IEEE Transactions on Circuits and Systems for Video Technology, 2008, 18(11): 1473-1488.

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