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Synthesis of Human Motion Using Kalman Filter

  • ChangWhan Sul
  • SoonKi Jung
  • Kwangyun Wohn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1537)

Abstract

This paper is concerned with the post-processing of motion-captured data. The post-processing is needed for several reasons: jerky motions due to sensor noise, violation of body constraints such as extraneous joint D.O.Fs, generation of new motion by editing existing motion data, and application of a motion to different character models. In this paper, the process of generating animated motion is viewed as a dynamic system, which takes the captured motion as input. Within a single Kalman filter framework, we were able to handle the following problems effiectively: satisfaction of physical constraints inherent to human body, user-specified kinematic constraints, motion transition, and noise reduction.

Keywords

Kalman Filter Motion Data Human Motion Kinematic Constraint Motion Transition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg1998 1998

Authors and Affiliations

  • ChangWhan Sul
    • 1
  • SoonKi Jung
    • 2
  • Kwangyun Wohn
    • 1
  1. 1.Department of Computer ScienceKAIST (Korea Advanced Institute of Science and Technology)Yusong-ku, TaejonKorea
  2. 2.Department of Computer EngineeringKyungpook National UniversityPuk-ku, TaeguKorea

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