| dc.description.abstract | Hand gestures play a significant role in HumanComputer Interaction(HCI) where traditional interaction method like Keyboard, Mouse or Joystick induce stress and fatigue to the user when interacting with computing environments. Technique like smart wearable glove, able to capture gestures more accurately compare to image- based recognition but it disturbs the user’s way of living. In this proposed light-based technique, simple motions of a hand like up, down, left, right, combine fingers motion like zoom in, zoom out, left rotation, right rotation, forward & Backward will be interfere with light-medium. The reflections of light from hand motional actions capture to process as interaction into computing environment. The technique, interact user’s hand motion with Infrared(IR) light medium. And through an array of Photodetectors(IR), the reflected light intensity measure to extract various distances from the array to hand and fingers. The sensor array directly coupled with the processing device, which convert light various intensities into voltages. Through programming and Machine Learning techniques, the proposed method able to identify the gestural aspect of the hand. The technique able to overcome the problems like background conditions, proper exposure towards the camera, start/stop aspect of the gesture and noise in image based HCI techniques. By continuous processing of IR reflections, the method able to identify various hand 3D motional gestures with easily compare to direct and indirect based interaction techniques. The technique easily able to customize for different users’ requirements and different environment to support human Computer Interaction. Further, this method supports simultaneous multiple user 3D interaction with the computing environment. | en_US |
