Using Technology Developed for Autonomous Cars to Help Navigate Blind People

Autonomous driving is currently a very active research area with virtually all automotive manufacturers competing to bring the first autonomous car to the market. This race leads to billions of dollars being invested in the development of novel sensors, processing platforms, and algorithms. In this paper, we explore the synergies between the challenges in self-driving technology and development of navigation aids for blind people. We aim to leverage the recently emerged methods for self-driving cars, and use it to develop assistive technology for the visually impaired. In particular we focus on the task of perceiving the environment in realtime from cameras. First, we review current developments in embedded platforms for real-time computation as well as current algorithms for image processing, obstacle segmentation and classification. Then, as a proof-of-concept, we build an obstacle avoidance system for blind people that is based on a hardware platform used in the automotive industry. To perceive the environment, we adapt an implementation of the stixels algorithm, designed for self-driving cars. We discuss the challenges and modifications required for such an application domain transfer. Finally, to show its usability in practice, we conduct and evaluate a user study with six blindfolded people.