Blind and low-vision (BLV) people rely on GPS-based systems for outdoor navigation. GPS's inaccuracy, however, causes them to veer off track, run into obstacles, and struggle to reach precise destinations. While prior work has made precise navigation possible indoors via hardware installations, enabling this outdoors remains a challenge. Interestingly, many outdoor environments are already instrumented with hardware such as street cameras. In this work, we explore the idea of repurposing existing street cameras for outdoor navigation. Our community-driven approach considers both technical and sociotechnical concerns through engagements with various stakeholders: BLV users, residents, business owners, and Community Board leadership. The resulting system, StreetNav, processes a camera's video feed using computer vision and gives BLV pedestrians real-time navigation assistance. Our evaluations show that StreetNav guides users more precisely than GPS, but its technical performance is sensitive to environmental occlusions and distance from the camera. We discuss future implications for deploying such systems at scale.

翻译：视障及低视力人群依赖基于GPS的系统进行户外导航。然而，GPS的不准确性常导致其偏离路线、碰撞障碍物，并难以抵达精确目的地。现有研究已通过硬件部署实现了室内精确导航，但在户外环境中实现该目标仍具挑战性。值得注意的是，许多户外环境已部署街景摄像头等硬件设施。本研究探索将现有街景摄像头改造用于户外导航的创新方案。通过联合视障用户、社区居民、商户及社区管理委员会等多方利益相关者，我们采用社区驱动的方法综合考虑技术与社会技术因素。最终构建的StreetNav系统运用计算机视觉技术处理摄像头视频流，为视障行人提供实时导航辅助。评估结果表明，相较于GPS，StreetNav能更精确引导用户，但其技术性能易受环境遮挡及与摄像头距离的影响。本文进一步探讨了此类系统规模化部署的未来发展方向。