Image processing based remote control with robot arm simulator

Motion estimation provides an attractive choice to cumbersome interface devices for human computer interaction (HCI). Worthy of note, visual recognition of hand gestures can help achieving in an easy and natural way for interaction between human and computer. The interfaces of HCI and other virtual reality systems depend on accurate, real-time hand and fingertip tracking for association between real objects and relative digital information. They cost expensively and complicated operations make them troublesome. We are developing a real-time, view-based gesture recognition system. Optical flow is estimated and segmented into motion fragments. Using artificial neural network (ANN), it can compute and estimate the motion of gesture. Comparing with the traditional approaches, theoretical and experimental results show that this method has more simple hardware and algorithm demands but more effectiveness. It can be used in remote control system for understanding the human body languages.