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Human motion database with a binary tree and node transition graphs

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Abstract

Database of human motion has been widely used for recognizing human motion and synthesizing humanoid motions. In this paper, we propose a data structure for storing and extracting human motion data and demonstrate that the database can be applied to the recognition and motion synthesis problems in robotics. We develop an efficient method for building a human motion database from a collection of continuous, multi-dimensional motion clips. The database consists of a binary tree representing the hierarchical clustering of the states observed in the motion clips, as well as node transition graphs representing the possible transitions among the nodes in the binary tree. Using databases constructed from real human motion data, we demonstrate that the proposed data structure can be used for human motion recognition, state estimation and prediction, and robot motion planning.

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Author information

Author notes

  1. Yoshifumi Yamaguchi

    Present address: Oracle Corporation Japan, Tokyo, Japan

Authors and Affiliations

  1. Disney Research, Pittsburgh, USA

    Katsu Yamane

  2. Dept. of Mechano-Informatics, University of Tokyo, Tokyo, Japan

    Yoshifumi Yamaguchi & Yoshihiko Nakamura

Authors
  1. Katsu Yamane
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  2. Yoshifumi Yamaguchi
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  3. Yoshihiko Nakamura
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Corresponding author

Correspondence to Katsu Yamane.

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Yamane, K., Yamaguchi, Y. & Nakamura, Y. Human motion database with a binary tree and node transition graphs. Auton Robot 30, 87–98 (2011). https://doi.org/10.1007/s10514-010-9206-z

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  • DOI: https://doi.org/10.1007/s10514-010-9206-z

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