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Combining fractal hourglass network and skeleton joints pairwise affinity for multi-person pose estimation

  • Yanmin Luo
  • Zhitong Xu
  • Peizhong Liu
  • Yongzhao Du
  • Jingming Guo
Article
  • 26 Downloads

Abstract

Human pose estimation, especially multi-person pose estimation, is vital for understanding human abnormal behavior. In this paper, we develop a fractal hourglass model to automatically regress human body joints, and propose a layered double-way inference algorithm to calculate the affinity between neighboring skeleton joints. Firstly, the original hourglass resident unit was replaced and the candidate skeleton joints location heatmap regression process was described. And then, we determine the specific body joints location and optimize the regression results. Next, the double-way conditional probabilities between adjacent joints is defined as joints pairwise affinity, and is applied to match adjacent human body part. What’s more, we adopt the spatial distance constraint to refine body joints matching result. Finally, we connect the best matching joints-pair, and iterate the process until all candidate joints are assigned into individual. Extensive experiments on the MPII multi-person subset and the COCO 2016 keypoints challenge show the effectiveness of our method, outperforming the second best method (Associative Embedding) by 0.45 and 1.20%.

Keywords

Fractal hourglass network Joints location heatmap regression Skeleton joints pairwise affinity Layered double-way inference Multi-person pose estimation 

Notes

Acknowledgements

We would like to gratitude the authors of the MPII human pose dataset and the team members of the COCO 2016 Keypoint Challenges. At the same time, we also thank our laboratory member’s assistance.

Funding

This work was supported by the grants from National Natural Science Foundation of China (Grant No. 61605048), the Talent project of Huaqiao University (Grant No. 14BS215), and Quanzhou scientific and technological planning projects of Fujian, China (Grant No. 2015Z120).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Yanmin Luo
    • 1
    • 2
  • Zhitong Xu
    • 1
    • 2
  • Peizhong Liu
    • 3
  • Yongzhao Du
    • 3
  • Jingming Guo
    • 4
  1. 1.College of Computer Science and TechnologyHuaqiao UniversityXiamenChina
  2. 2.Key Laboratory for Computer Vision and Pattern Recognition of Xiamen CityHuaqiao UniversityXiamenChina
  3. 3.College of EngineeringHuaqiao UniversityQuanzhouChina
  4. 4.Department of Electrical EngineeringNational Taiwan University of Science and TechnologyTaipeiTaiwan

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