This project aims to develop a computer vision-based (stereo vision or RGB-D camera) navigation system for the visually impaired.
This system is expected to enable the visually impaired to extend the range of their activities compared to that provided by conventional aid device, such as white cane. In order to extract orientational information of the blind users, we incorporate visual odometry and feature based metric-topological SLAM into our system. We build a vicinity map based on dense 3D data obtained from computer vision system, and perform path planning to provide the visually impaired with 3D traversability on the map. The 3D traversability analysis helps subjects steer away from obstacles in the path. A vest-type interface consisting of four microvibration motors delivers queues for real-time navigation with obstacle avoidance. Our system operates at 15Hz, and helps the visually impaired improve the mobility performance in a cluttered environment.
<Fig. 1> System overview: Image/3D information acquisition device, SLAM Process, and a feedback system.
[pdf] version available.
 Young Hoon Lee, Gerard Medioni, A RGB-D camera Based Navigation for the Visually Impaired,
RSS 2011 RGB-D: Advanced Reasoning with Depth Camera Workshop, Los Angeles, Jun 2011.
 Indoor navigation using stereo camera
 Indoor navigation using RGBD sensor (our system)
 Best Research Demo Award, 2nd Annual Ming Hsieh Department of Electrical Engineering Research Festival, USC
 Finalist, Cornell Cup USA, presented by Intel.
 USC Viterbi magazine
 The Economic Times: How Image Processing will move the world
 L.A. Business Journal