Skeleton-dominated two stream graph convolutional networks for skeleton-based action recognition

Yuwen Luo; Zengfu Wang

doi:10.1117/12.3033795

13 June 2024 Skeleton-dominated two stream graph convolutional networks for skeleton-based action recognition

Yuwen Luo, Zengfu Wang

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 1318054 (2024) https://doi.org/10.1117/12.3033795
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

In daily life and industrial development, action recognition have been widely used. However, most of the current RGBbased action recognition models focus too much on background information and not on the posture information and action information of the behavior, which may cause many problems in the industry and even be detrimental to the development of the industry. For this purpose, we propose a Two-stream network architecture that fuses the skeletonbased posture and action information and the RGB-based fine-grained image information. And the effect of our model was verified on the Mimetics data set which eliminated background interference.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuwen Luo and Zengfu Wang "Skeleton-dominated two stream graph convolutional networks for skeleton-based action recognition", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 1318054 (13 June 2024); https://doi.org/10.1117/12.3033795

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KEYWORDS

RGB color model

Action recognition

Data modeling

Video

Transformers

Motion models

Education and training

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