Active Vision: From Theory to Application

Abstract

An overview of known works in active vision area and our recent results on application of the foveal visual preprocessor to detect the head motion parameters are presented. In overview, the main directions of research and development in the field of artificial foveal active vision have been considered. It is justified that: (i) for a successful solution of complex problems in this area and creation of universal systems based on active foveal vision, it is necessary to develop new technologies and platforms for the experimental study of various aspects of active foveal vision in detail; (ii) at present, software implementations of the foveal principles of visual information processing already contribute to solving particular applied problems of computer vision. In computer simulation, detection of the initial moment of head motion was evaluated by means of foveal visual preprocessor. In this neural network, each pair of excitatory and inhibitory neurons has common center, different sizes of their receptive fields and time delay. To test network performance, synthetic video of facial image sequences from SYLAHP database monitoring the head motion were used. It was shown that the U^E amplitude and polarity qualitatively correspond to face motion amplitude and direction. The initial front of U^E changes corresponding to quick motion of head was equal to 12 ms in all cases (n = 46). Video of real face images with graduated turns was tested too to estimate quantitative relation between output function of excitatory neuron and turn degree. It was revealed that this relation is equal to 40 U^E/degree. Future steps of research in this direction have been shortly discussed.