HCI using hand gesture recognition for Digital Sand Model

The Digital Sand Model is a tactical exercise without troops, which gives a bird's view of the terrain and allows the users to work on the battle planning and management. Interaction plays a substantial role in such training setups. In this paper we designed and developed an intuitive and "hands-free" human computer interaction for the DSM. The captured image is pre-processed for enhancing the hand object in the image. Specific features need to be extracted for fast and accurate recognition of the hand gesture. Two sets of feature vectors are explored in this paper, namely, Hu moments and hand contour. These features are classified using two different classifiers, namely, SVM and HMM and their performances are compared and analyzed.