Human Motion Simulation and Action Corpus

  • Gang Zheng
  • Wanqing Li
  • Philip Ogunbona
  • Liju Dong
  • Igor Kharitonenko
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4561)


Acquisition of large scale good quality training samples is becoming a major issue in machine learning based human motion analysis. This paper presents a method to simulate continuous gross human body motion with the intention to establish a human motion corpus for learning and recognition. The simulation is achieved by a temporal-spatialtemporal decomposition of human motion into actions, joint actions and actionlets based on the human kinematic model. The actionlet models the primitive moving phase of a joint and represents the muscle movement governed by kinesiological principles. Joint actions and body actions are constructed from actionlets through constrained concatenation and synchronization. Methods for concatenation and synchronization are proposed in this paper. An action corpus with small number of action vocabularies is created to verify the feasibility of the proposed method.


Human Motion Actions Simulation Motion Editing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Gang Zheng
    • 1
  • Wanqing Li
    • 1
  • Philip Ogunbona
    • 1
  • Liju Dong
    • 1
    • 2
  • Igor Kharitonenko
    • 1
  1. 1.School of Computer Science and Software Engineering, University of WollongongAustralia
  2. 2.College of Information Engineering, Shenyang UniversityP.R. of China

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