Intersection Navigation for People with Visual Impairment

Utilizing RGB-Depth images acquired by a wearable system, we propose an integrated assistive navigation for visually impaired people at urban intersection, which provides with crosswalk position (where to cross roads), crossing light signal (when to cross roads) and pedestrian state (whether safe to cross roads). Verified by the experiment results on datasets and in field, the proposed approach detects multiple targets at urban intersections robustly and provides visually impaired people with effective assistance.