Research advanced in human pose estimation based on deep learning

Ye Xia; Xinxue Jiang; Liaowenjin Yan

doi:10.1117/12.2667904

28 March 2023 Research advanced in human pose estimation based on deep learning

Ye Xia, Xinxue Jiang, Liaowenjin Yan

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125660J (2023) https://doi.org/10.1117/12.2667904
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

Human pose recognition is a current research hot spot, which aims to detect the information of human joints, orientations and scales from images or videos and predict the specific pose of the human body based on all the key point information. Benefiting from the rapid evolution of deep learning, target detection algorithms based on convolutional neural networks have achieved breakthroughs in both accuracy and efficiency. On the basis of detailed literature research and analysis, this paper provides a comprehensive evaluation of the research progress of human pose estimation. Specifically, we mainly introduce the classification of human action poses and the methods of human action pose recognition, including the design ideas, basic framework and advantages and disadvantages of representative recognition methods. Finally, we summarize the main challenges and give an outlook on the future research development of object detection.

Citation Download Citation

Ye Xia, Xinxue Jiang, and Liaowenjin Yan "Research advanced in human pose estimation based on deep learning", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125660J (28 March 2023); https://doi.org/10.1117/12.2667904

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