Gesture recognition using sparse code of Hierarchical SOM

We propose an approach to recognize time-series gesture partems wilh Hierarchical Self-Organizing Map(HSOM). Dlle of the key issue of the time-series ponem recognition is to absorb the time Variant appropriately and to make clusters which indude the same gesture class. In our approach. we arrange the SOM hierarchically. In each layer of the SOM the time-series pattenrs divided into some periods; postures, gesture elements and gestures. They are learned in each layer of HSOM. For example, postures and learned in the first layer, gesture elements are learned in the second layer and so on. Using the sparse code in the bottom layer, the SOM can perform time invariant recognition of the gesture elemems and gestures.