Depth‐based end‐to‐end deep network for human action recognition-Reference-Cited by-同舟云学术

Depth‐based end‐to‐end deep network for human action recognition

Published:2018-11-23 Issue:1 Volume:13 Page:15-22
ISSN:1751-9640
Container-title:IET Computer Vision
language:en
Short-container-title:IET Computer Vision

Author:

Chaudhary Sachin¹^ORCID,Murala Subrahmanyam¹

Affiliation:

1. Computer Vision and Pattern Recognition Laboratory, IIT RoparRupnagarPunjabIndia

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cvi.2018.5020

Reference55 articles.

1. 3D human action recognition using a single depth feature and locality‐constrained affine subspace coding;Liang C.;IEEE Trans. Circuits Syst. Video Technol.,2017

2. Human action recognition using Adaptive Hierarchical Depth Motion Maps and Gabor filter

3. Towards Understanding Action Recognition

4. HMDB: A large video database for human motion recognition

5. Soomro K. Zamir A.R. Shah M.: ‘UCF101: a dataset of 101 human actions classes from videos in the wild’ arXiv Prepr. arXiv1212.0402 2012

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