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Hierarchical topology based hand pose estimation from a single depth image

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Abstract

Hand pose estimation benefits large human computer interaction applications. The hand pose has high dimensions of freedom (dof) for joints, and various hand poses are flexible. Hand pose estimation is still a challenge problem. Since hand joints on the hand skeleton topology model have strict relationships between each other, we propose a hierarchical topology based approach to estimate 3D hand poses. First, we determine palm positions and palm orientations by detecting hand fingertips and calculating their directions in depth images. It is the global topology of hand poses. Moreover, we define connection relationships of finger joints as the local topology of hand model. Based on hierarchical topology, we extract angle features to describe hand poses, and adopt the regression forest algorithm to estimate 3D coordinates of hand joints. We further use freedom forrest algorithm to refine ambiguous poses in estimation to solve error accumulation problem. The hierarchical topology based approach ensures estimated hand poses in a reasonable topology, and improves estimation accuracy. We evaluate our approach on two public databases, and experiments illustrate its efficiency. Compared with state-of-the-art approaches, our approach improves estimation accuracy.

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Acknowledgements

This research is supported by the Natural Science Foundation of China (NSFC) under grant No. 61305043 and grant No. 61673088. It is also supported by the Natural Science Foundation of China (NSFC) under grant No.61572108.

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Authors and Affiliations

  1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Yanli Ji & Haoxin Li

  2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Yang Yang

  3. The 16th Institute, China Aerospace Science and Technology Corporation, Xi’an, China

    Shuying Li

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  1. Yanli Ji
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  2. Haoxin Li
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  3. Yang Yang
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  4. Shuying Li
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Correspondence to Yanli Ji.

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Ji, Y., Li, H., Yang, Y. et al. Hierarchical topology based hand pose estimation from a single depth image. Multimed Tools Appl 77, 10553–10568 (2018). https://doi.org/10.1007/s11042-017-4651-8

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  • DOI: https://doi.org/10.1007/s11042-017-4651-8

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