Abstract
In this study, we propose an evolutionary fuzzy neural network based on structured learning for gesture recognition. In general, processing for gesture recognition consists of feature extraction part and gesture classification part. In most of the works, they are independently designed and evaluated by their own criteria. However, it is difficult to design the components without considering the relationship between each component. Structured learning can be a solution to the problem. One of the primary aims of structured learning is a mutual adjustment to improve the classifier's generalization ability. We use a neuro-fuzzy system for the classification of human gesture and apply an evolutionary approach to parameter tuning and pruning of membership functions.
