Collision Detection for Visually Impaired from a Body-Mounted Camera

Shrinivas Pundlik, Matteo Tomasi, Gang Luo; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2013, pp. 41-47

A real-time collision detection system using a bodymounted camera is developed for visually impaired and blind people. The system computes sparse optical flow in the acquired videos, compensates for camera self-rotation using external gyro-sensor, and estimates collision risk in local image regions based on the motion estimates. Experimental results for a variety of scenarios involving static and dynamic obstacles are shown in terms of timeto-collision and obstacle localization in test videos. The proposed approach is successful in estimating collision risk for head-on obstacles as well as obstacles that are close to the walking paths of the user. An end-to-end collision warning system based on inputs from a video camera as well as a gyro-sensor has been implemented on a generic laptop and on an embedded OMAP-3 compatible platform. The proposed embedded system represents a valuable contribution toward the development of a portable vision aid for visually impaired and blind patients.