Robust estimation of human posture using incremental learnable Self-Organizing Map

We propose an approach to improve the accuracy of estimating feature points of human body on a vision-based motion capture system (MCS) by using the Variable-Density Self-Organizing Map (VDSOM). The VDSOM is a kind of Self-Organizing Map (SOM) and has an ability to learn training samples incrementally. We let VDSOM learn 3-D feature points of human body when the MCS succeeded in estimating them correctly. On the other hand, one or more 3-D feature point could not be estimated correctly, we use the VDSOM for the other purpose. The SOM including VDSOM has an ability to recall a part of weight vector which have learned in the learning process. We use this ability to recall correct patterns and complement such incorrect feature points by replacing such incorrect feature points with them.