Clustering for Extracted Motion Patterns Based on Sensitivity of Human and Representative Pattern Generation

Abstract

In this paper, we propose the technique of clustering for motion patterns extracted from continuous input. Traditional techniques obtain clusters using the distance of each motions. Obtained clustering result tended not to be familiar for human sensitivity. In order to extract the rule for the motion categorization according to human sensitivity, we measured the human sensitivity to the motion appearance changed by position, scale, speed, and so on. Sensitivity parameters are applied to proposed clustering method. Representative motion patterns for corresponding basic motion clusters are generated according to the appearance trend. Experimental result shows the adequacy of proposed clustering method based on human sensitivity for motion appearance.