Eye movement based on short-term memory optical flow image

The pixel distribution density of human vision is higher near the fovea, becoming lower toward the periphery. It is also reported that the optical flow has an important role in understanding the surrounding situation. This paper proposes the eye movement model based on fovea vision, short-term memory of the optical flow, and parallel execution of the tasks. In the realization of the eye movement while driving in an environment where there are few vehicles, both the narrow-range eye movement to shift the viewpoint to the next edge along the road, and the wide-range eye movement to understand the environmental situation, must be realized. In order to adjust the range of eye movement according to the task, short-term memory depending on the task is considered. It is shown that a wide range of view can be realized, by using the short-term memory image, which is generated based on the low-level features derived from the optical flow. The eye movement while driving in a situation where there are few vehicles is actually simulated in a simple way, and the usefulness of the proposed model is demonstrated.