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We propose a method using an auto encoder multilayered neural network that can classify and extract small scale difference in human behavior. The video images of ping-pong swing forms were recorded by the high-speed camera and analyzed differences in movement depending on a different cluster obtained by k-means method applied to orbital data in the feature space. We confirmed that the orbits in the feature space represent some kinds of characteristics of swing motions and showed the possibility of automatic detection of human behavior by focusing on orbital features created in the middle layer of an auto encoder neural network.

Proposing a Classification Method of Human Behavior Focusing on Orbital Characteristic on Feature Space in a Neural Network