Detect and Approach: Close-Range Navigation Support for People with Blindness and Low Vision

• URL: http://arxiv.org/abs/2208.08477v1
• Date: Wed, 17 Aug 2022 18:38:20 GMT
• Title: Detect and Approach: Close-Range Navigation Support for People with Blindness and Low Vision
• Authors: Yu Hao, Junchi Feng, John-Ross Rizzo, Yao Wang, Yi Fang
• Abstract summary: People with blindness and low vision (pBLV) experience significant challenges when locating final destinations or targeting specific objects in unfamiliar environments. We develop a novel wearable navigation solution to provide real-time guidance for a user to approach a target object of interest efficiently and effectively in unfamiliar environments.
• Score: 13.478275180547925
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: People with blindness and low vision (pBLV) experience significant challenges when locating final destinations or targeting specific objects in unfamiliar environments. Furthermore, besides initially locating and orienting oneself to a target object, approaching the final target from one's present position is often frustrating and challenging, especially when one drifts away from the initial planned path to avoid obstacles. In this paper, we develop a novel wearable navigation solution to provide real-time guidance for a user to approach a target object of interest efficiently and effectively in unfamiliar environments. Our system contains two key visual computing functions: initial target object localization in 3D and continuous estimation of the user's trajectory, both based on the 2D video captured by a low-cost monocular camera mounted on in front of the chest of the user. These functions enable the system to suggest an initial navigation path, continuously update the path as the user moves, and offer timely recommendation about the correction of the user's path. Our experiments demonstrate that our system is able to operate with an error of less than 0.5 meter both outdoor and indoor. The system is entirely vision-based and does not need other sensors for navigation, and the computation can be run with the Jetson processor in the wearable system to facilitate real-time navigation assistance.

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