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DEVS-based Modeling of a Human Motion Data Synthesis System based on Motion Capture Data

This paper presents a DEVS-based model for a human motion data synthesis system. The model includes some major components of the human motion control system such as brain, spinal cord, and body. The system is designed to produce the output data in the form of motion capture data. The proposed model and the output data produced can be widely applied in areas such as robotics and multimedia (animation). The simulations carried out illustrate the performance of such a model which is capable of accurate mimicking of the human motion control system. The model is capable of taking into account minute features either related to actor characteristics, or even noise. In the end, we have shown that discrete event modeling is a very suitable means of describing human motion control and synthesis systems.