We propose a machine learning-based system named “Computational Foresight” that can forecast human body motion 0.5 seconds before the actual motion in real-time. This forecasting system can be used to estimate human gestures in advance to the actual action for reducing delays in interactive system. In addition, the system can be applied to instruct sports actions properly, and prevent elderly from falling to the ground, and so on. Proposed system detects 25 human body joints to use those data for input dataset of machine learning. We created 5-layered neural network to estimate human body motion in real-time. In our experiment, we measured jump motions of subjects for learning. In our evaluation, the prototype system scored that the center of gravity of whole body can be forecasted 0.5 sec before with its accuracy of 12.8 cm.
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