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High-order local connection network for 3D human pose estimation based on GCN

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Abstract

Theskeleton structure of human body is a natural undirected graph. Being applied to 3D body pose estimation, graph convolutional network (GCN) has achieved good results. However, the vanilla GCN ignores the differences between joints and the connections between joints with different distances. Based on the above two problems, we propose High-order Local Connection Network (HLCN) for 3D human pose estimation. On one hand, different filters for different joints are assigned to produce different weights. On the other hand, the feature of multi-hop joints synthetically is gathered into HLCN. Furthermore, we study different methods of fusing these multi-hop features and compare their performance. The new network not only takes the differences between the joints in the human skeleton into consideration, but also captures the remote dependencies between human joints. The experiment suggests that this method is superior to vanilla GCN and achieve state-of-the-art performance. The average error on the H36M dataset is 50.9 mm.

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Acknowledgements

This work was supported in part by the Key Program of NSFC (Grant No.U1908214), Dalian University Scientific Research Platform Project (No. 202101YB03), Special Project of Central Government Guiding Local Science and Technology Development (Grant No. 2021JH6/10500140), Program for the Liaoning Distinguished Professor, Program for Innovative Research Team in University of Liaoning Province, Dalian and Dalian University, and in part by the Science and Technology Innovation Fund of Dalian (Grant No. 2020JJ25CY001).

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Authors and Affiliations

  1. National and Local Joint Engineering Laboratory of Computer Aided Design, School of Software Engineering, DaLian University, Dalian, 116622, LiaoNing, China

    Wei Wu, Dongsheng Zhou, Qiang Zhang & Jing Dong

  2. School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, LiaoNing, China

    Dongsheng Zhou, Qiang Zhang & Xiaopeng Wei

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  1. Wei Wu
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Correspondence to Jing Dong or Xiaopeng Wei.

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Wu, W., Zhou, D., Zhang, Q. et al. High-order local connection network for 3D human pose estimation based on GCN. Appl Intell 52, 15690–15702 (2022). https://doi.org/10.1007/s10489-022-03312-x

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