A WearableCamera System for Pointing Gesture Recognition and Detecting Indicated Objects

We propose a system for pointing gesture recognition and detecting indicated objects by using a vision sensor. By using random sampling and importance sampling, our method can track hands and estimate hand positions in real-time. By using the concepts of a cognitiveorigin and a reference plane, our system can also detect a direction to an indicated object. We use an omnidirectional vision sensor in order to cover the wide range of hand operations and movement of indicated objects. The camera is mounted on the head, which enables the system to be tolerant of the occlusion problem. The method for detecting an indicated object uses a linear model with the concepts of a cognitive origin and a reference plane.