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.
This work is partially supported by the Electronics & Telecommunications Research Institute (ETRI) under constract ETRI-8MG2600, and Center for AI Research (CAIR), KAIST.
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© 1998 Springer-Verlag Berlin Heidelberg1998
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Sul, C., Jung, S., Wohn, K. (1998). Synthesis of Human Motion Using Kalman Filter. In: Magnenat-Thalmann, N., Thalmann, D. (eds) Modelling and Motion Capture Techniques for Virtual Environments. CAPTECH 1998. Lecture Notes in Computer Science(), vol 1537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49384-0_8
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DOI: https://doi.org/10.1007/3-540-49384-0_8
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