StreetNav: Leveraging Street Cameras to Support Precise Outdoor Navigation for Blind Pedestrians
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Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Sep 2023.
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Citing papers per year: 2024: 2; 2025: 3; 2026: 2.
7 papers.
- 2025CitySeeker: How Do VLMS Explore Embodied Urban Navigation With Implicit Human Needs?cited by 8
- 2024Can LLMs Generate Human-Like Wayfinding Instructions? Towards Platform-Agnostic Embodied Instruction Synthesiscited by 6
- 2025mmWalk: Towards Multi-modal Multi-view Walking Assistancecited by 3
- 2024The Streetscape Application Services Stack (SASS): Towards a Distributed Sensing Architecture for Urban Applicationscited by 0
- 2025"Does the cafe entrance look accessible? Where is the door?" Towards Geospatial AI Agents for Visual Inquiriescited by 0
- 2026Touvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environmentscited by 0
- 2026NavAble: A Large-Scale Dataset and Synthetic Data Generation Pipeline for Blind Navigationcited by 0
- 2026NavAble: A Large-Scale Dataset and Synthetic Data Generation Pipeline for Blind Navigation14 Oct 2026
- 2026Touvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environments18 Sep 2026
- 2025CitySeeker: How Do VLMS Explore Embodied Urban Navigation With Implicit Human Needs?18 Dec 2025
- 2025mmWalk: Towards Multi-modal Multi-view Walking Assistance13 Oct 2025
- 2025"Does the cafe entrance look accessible? Where is the door?" Towards Geospatial AI Agents for Visual Inquiries21 Aug 2025
- 2024The Streetscape Application Services Stack (SASS): Towards a Distributed Sensing Architecture for Urban Applications29 Nov 2024
- 2024Can LLMs Generate Human-Like Wayfinding Instructions? Towards Platform-Agnostic Embodied Instruction Synthesis18 Mar 2024