Gaze movement control neural network based on multidimensional topographic class grouping

Abstract

Target search is an important ability of the human visual system. One major problem is that the real human visual cognitive process, which requires only few samples for learning, has abilities of inference with obtained knowledge for searching when he meets the new target. Based on the Topographic Class Grouping (TCG) [1] and a series of models of Visual Perceiving and Eyeball-Motion Controlling Neural Networks [2-5], we make effective improvements to the models, by incorporating the cerebral self-organizing feature mapping function in terms of multidimensional TCG. In this paper, we propose the gaze movement control neural network based on multidimensional TCG. Experiments show that gaze movement control neural network by adding a block of multidimensional TCG and by self-organizing visual field image features-spatial relationship clustering achieves the visual inference and stable results on the target search tasks.