Active vision system based on human eye saccadic movement

We propose a new active vision system that mimics a saccadic movement of hu man eye. It is implemented based on a new computational model using neural networks. In this model, the visual pathway was divided in order to categor ize a saccadic eye movement into three parts. each of which was then indivi dually modeled using different neural networks to reflect a principal funct ionality of brain structures related with the saccadic eye movement in our brain. Initially. the visual cortex for saccadic eye movements was modeled using a self-organizing feature map, then a modified learning vector quanti zation net work was applied to imitate the activity of the superior collicu lus relative to a visual stimulus. In addition. a multilayer recurrent neur al network, which is learned by an evolutionary computation algorithm, was used to model the visual pathway from the superior colliculus to the oculom otor neurons. Results from a computer simulation show that the proposed com putational model is effective in mimicking the human eve movements during a saccade. Based on the proposed model, an active vision system using a CCD type camera and motor system was developed and demonstrated with experiment al results.