Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 08, 2016 - June 11, 2016
Man-machine interface based on the biological signals from head is essential to the development of life support and personal assistance tools for handicapped people. We believe that user-adaptive recognition techniques are necessary for the spread of such life support tools and that the generalization ability of the recognition techniques is indispensable for achieving user adaptation. In this work, we propose combination of a parametric t-SNE and a 3-layer neural network for enhancing the generalization ability of our expression recognition system based on biological signals from head. Through experiment in real environment, we confirm the validity of our method.
