On Natural Motion Editing by a Geometric Mean Filter

  • Jin Ok Kim
  • Chang Han Oh
  • Chin Hyun Chung
  • Jun Hwang
  • Woongjae Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2668)


Recently, motion capture has become one of the most promising technologies in animation. Realistic motion data can be captured by recording the movement of a real actor with an optical or magnetic motion capture system. A motion library that is an archive of reusable motion clips is also commercially available. This paper deals with motion editing by a geometric mean filter. Since the captured motion has some noises that cause a jerky motion, it needs a smoothing process to make it natural. A geometric mean filter is proposed to produce natural motions without jerky motions. Experimental results show that the geometric mean filter can effectively remove noises that cause a jerky motion and it can guarantee the most natural motions among various spatial filters. This method could be applied to the various fields such as real time animation, virtual reality applications, 3D applications, and etc.


Motion Capture Natural Motion Unit Quaternion Virtual Human Virtual Reality Application 
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 Heidelberg 2003

Authors and Affiliations

  • Jin Ok Kim
    • 1
  • Chang Han Oh
    • 2
  • Chin Hyun Chung
    • 2
  • Jun Hwang
    • 3
  • Woongjae Lee
    • 3
  1. 1.School of Information and Communication EngineeringSungkyunkwan UniversitySuwon, Kyunggi-doKOREA
  2. 2.Department of Information and Control EngineeringKwangwoon UniversityNowon-gu, SeoulKOREA
  3. 3.Division of Information and Communication EngineeringSeoul Women’s UniversityNowon-gu, SeoulKOREA

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