Obstacle detection for pedestrians with a visual impairment based on 3D imaging


According to theWorld Health Organisation, 285 million people live with a visual impairment. Despite the fact that many efforts have been made recently, there is still no computerguided system that is reliable, robust and practical enough to help these people to increase their mobility. Motivated by this shortcoming, we propose a novel obstacle detection system to assist the visually impaired. This work mainly focuses on indoor environments and performs classification of typical obstacles that emerge in these situations, using a 3D sensor. A total of four classes of obstacles are considered: walls, doors, stairs and a residual class (which covers loose obstacles and bumpy parts on the floor). The proposed system is very reliable in terms of the detection accuracy. In a realistic experiment, stairs are detected with 100% true positive rate and 8.6% false positive rate, while doors are detected with 86.4% true positive rate and 0% false positive rate.