Hand data glove: A new generation real-time mouse for Human-Computer Interaction

This Human-Computer Interaction (HCI) is a field in which the developer makes a user friendly system. In this paper, a real-time Human-Computer Interaction based on the hand data glove and k-NN classifier for gesture recognition is proposed. HCI is becoming more and more natural and intuitive to be used. The important part of body that is hand is most frequently used as interaction in digital environment and thus complexity and flexibility of motion of hand is a research topic. To recognize hand gesture accurately and successfully data glove is used. Here, glove is used to capture current position and angle of hand and fingers, and further classify it using k-NN classifier. The gestures classified are clicking, dragging, rotating, pointing and ideal position. Recognizing these gestures relevant actions are taken, such as air writing and 3D sketching by tracking the path. This can be also used in the controlling of an image browser tool using data glove. The results show that glove used for interaction is better than normal static keyboard and mouse as the interaction process is more accurate and natural. Also it enhances the user's interaction and immersion feeling.