Research on intelligent estimation of human posture in multiplayer complex scenarios

Xiaodong Hou; Tingjun Wang; Xu Zou; Xinying Yang; Yiheng Yang; Haosong Li

doi:10.1117/12.3055740

2 December 2024 Research on intelligent estimation of human posture in multiplayer complex scenarios

Xiaodong Hou, Tingjun Wang, Xu Zou, Xinying Yang, Yiheng Yang, Haosong Li

Proceedings Volume 13443, Fifth International Conference on Computer Vision and Information Technology (CVIT 2024); 1344305 (2024) https://doi.org/10.1117/12.3055740
Event: 2024 5th International Conference on Computer Vision and Information Technology (CVIT 2024), 2024, Beijing, China

Abstract

The advent of deep learning technology has significantly expanded in the application of human pose estimation in various fields such as image processing and human-computer interaction. Nonetheless, the current techniques have limitations in their ability to accurately recognize poses in multi-person scenes, occlusion situations, and under varying lighting conditions. This paper introduces a novel approach for human bone recognition that is applicable to complex environments. The aim is to improve recognition accuracy and robustness in these scenarios. The method utilizes a deep learning model that incorporates multi-branch structure and occlusion techniques. It was tested on numerous video datasets, and the results demonstrate its superior bone recognition ability in complex scenes. Additionally, it exhibits high adaptability and accuracy in multi-person scenes, occlusion situations, and lighting changes.

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

Citation Download Citation

Xiaodong Hou, Tingjun Wang, Xu Zou, Xinying Yang, Yiheng Yang, and Haosong Li "Research on intelligent estimation of human posture in multiplayer complex scenarios", Proc. SPIE 13443, Fifth International Conference on Computer Vision and Information Technology (CVIT 2024), 1344305 (2 December 2024); https://doi.org/10.1117/12.3055740

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