A salient information processing system for bionic eye with application to obstacle avoidance.

In this paper we present a visual processing system for bionic eye with a focus on obstacle avoidance. Bionic eye aims at restoring the sense of vision to people living with blindness and low vision. However, current hardware implant technology limits the image resolution of the electrical stimulation device to be very low (e.g., 100 electrode arrays, which is approx. 12 × 9 pixels). Therefore, we need a visual processing unit that extracts salient information in an unknown environment for assisting patients in daily tasks such as obstacle avoidance. We implemented a fully portable system that includes a camera for capturing videos, a laptop for processing information using a state-of-the-art saliency detection algorithm, and a head-mounted display to visualize results. The experimental environment consists of a number of objects, such as shoes, boxes, and foot stands, on a textured ground plane. Our results show that the system efficiently processes the images, effectively identifies the obstacles, and eventually provides useful information for obstacle avoidance.