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Dynamic attack motion prediction for kendo agent | IEEE Conference Publication | IEEE Xplore

Dynamic attack motion prediction for kendo agent


Abstract:

A motion prediction method using Gaussian Mixture Models (GMM) is applied to a kendo agent (Kendo is a traditional Japanese martial art). Human player motion is measured ...Show More

Abstract:

A motion prediction method using Gaussian Mixture Models (GMM) is applied to a kendo agent (Kendo is a traditional Japanese martial art). Human player motion is measured by a motion capture system, using markers attached to each of the player's joints. Measurement information is converted to a state vector with Euler angles to indicate orientation of the sword and orientation of each part of the player's body. To model the motion as a nonlinear dynamical system, GMMs are generated from a demonstration set when an opponent is attacked. The efficiency of the proposed method is experimentally verified.
Date of Conference: 14-18 September 2014
Date Added to IEEE Xplore: 06 November 2014
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ISSN Information:

Conference Location: Chicago, IL, USA

References

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