Extraction of Keyframe from Motion Capture Data Based on Motion Sequence Segmentation

Linear time-invariant system is used to derive an explicit mapping between the high-dimensional motion capture data and the low-dimensional state variables.A similarity metric is defined to measure the difference between different poses in the low-dimensional state space,and then the method of mean squared error is employed to divide the motion sequence into a sequence of concatenated segments.The poses at these segmentation points are then defined as keyframes.Experimental results show that the extracted keyframes by our method can give a good visual summarization of the original motion sequence.