A deep learning based outdoor walking assistive system for the visually impaired
Summary We provides a wearable device for the visually impaired to walk outdoors. By the deep learning network, the system can recognize and guide the visually impaired to walk on safe areas such as sidewalks and crosswalk. In addition, it can recognize the types of common obstacles and guide the visually impaired to avoid it in advance. Finally, we can convert the Google Maps route into easy-to-understand voice prompts instruction to guide the visually impaired to move in the right direction.

We proposed a wearable device that can recognize and guide the visually impaired to walk on the sidewalk or crosswalk. We proposed easily understanding instructions to guide the visually impaired to walk outdoors, avoid obstacles, and go to the destination. Combining sensor information and object detection network, we provided a robust obstacle avoidance method and a convenient store sign-approaching method to guide the visually impaired to approach the convenience store to solve the problem of insufficient GPS location.

This technology can help the visually impaired and is a powerful product for the assistive device market for the visually impaired. Except for the white cane, this product is one of the most reliable assistive devices for the visually impaired congenital or acquired.
Technical Film
Keyword Intelligent Information System Environmental control and perception technology Interdisciplinary integration
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