Face Detection for AIBO Using RBF Network and Particle Filter
Kohki Abiko, Hironobu Fukai, Yasue Mitsukura, Minoru Fukumi, Masahiro Tanaka · Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications · 2010
We propose a face-tracking system for AIBO by using skin colors. If AIBO finds a face, AIBO can acquire a situation 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 skin color area, based on the motion pattern of a face. And, in order to show the effectiveness of the proposed method, we perform experiments. In various light conditions, we have relatively good results of the skin color recognition. Furthermore, we show the output value distribution in a color space. We can see 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 a face in various noisy environments by using the particle filter. Finally, we achieve the face tracking system for AIBO in a real system. It will be shown that AIBO can detect and track a face in many kinds of light conditions.