Object recognition via recognition of finger pointing actions

We propose an object recognition method in which the identity of objects is determined by observing the finger pointing action of persons. The system determines the head and hands regions, tracks them in real time, and verifies them through an analysis of 3D data points. Then it determines the pointing direction and intersects it with an environment model. Intersection computations are based on potential field models for both the finger pointing process and the object representations.