Adaptive Body Part ROI with Triple Stream Approach for Human Action Recognition-Reference-Cited by-同舟云学术

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Adaptive Body Part ROI with Triple Stream Approach for Human Action Recognition

Published:2024-06-19 Issue: Volume:1 Page:79-85
ISSN:
Container-title:2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE)
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Author:

Tepsan Worawit¹,Sooksatra Sorn²,Lueangwitchajaroen Pitiwat³,Watcharapinchai Sitapa²

Affiliation:

1. International College of Digital Innovation Chiang Mai University,Chiang Mai,Thailand

2. National Electronic and Computer Technology Center (NECTEC) National Science and Technology Development Agency (NSTDA),Pathum Thani,Thailand

3. The University of Nottingham,Department of Physics and Astronomy,Nottingham,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10613603/10613624/10613745.pdf?arnumber=10613745

Reference21 articles.

1. Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points

2. Body and Hand–Object ROI-Based Behavior Recognition Using Deep Learning

3. OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields

4. P-CNN: Pose-Based CNN Features for Action Recognition

5. Revisiting Skeleton-based Action Recognition

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