Face detection on AIBO by using the RBF and particle filtering

We propose a face-tracking system for AIBO by using skin colors. If AIBO finds a face, AIBO can acquire a condition of user and act more actively. In this paper, we focus on the human-face, which has many kinds of characteristic parts in a human (i.e. age, gender, expression). We detect a face using the radial basis function (RBF) network and the particle filter. First, we use the RBF network for the purpose of skin color recognition. Second, we use the particle filter in order to detect a face in the skin color area, based on the motion pattern of a face. Moreover, in order to show the effectiveness of the proposed method, we perform computer simulations. In various light conditions, we have relatively good results of the skin color recognition. Furthermore, we show a possibility of little false recognitions in unknown color, using the RBF network. Moreover, by applying moving images to the particle filters, we detect and track the face in various noisy environments. Finally, we achieve the face tracking system for AIBO in a real system. It will be shown that AIBO can detect and track the face.