Towards Fine-Grained Sidewalk Accessibility Assessment with Deep Learning: Initial Benchmarks and an Open Dataset

Alex Liu, Kevin Wu, Minchu Kulkarni, Mikey Saugstad, Peyton Rapo, Jeremy Freiburger, Maryam Hosseini, Chu Li, Jon E. Froehlich

Extended Abstract ASSETS 2024 To Appear | Acceptance Rate: 66.7% (58 / 87)

keywords: computer vision, sidewalk assessment, sidewalk accessibility, vision transformers, obstacle detection

PDF | doi | Citation | Deep Learning for Sidewalk Assessment • Project Sidewalk

Scaling Crowd+AI Sidewalk Accessibility Assessments: Initial Experiments Examining Label Quality and Cross-city Training on Performance

Michael Duan, Sho Kiami, Logan Milandin, Johnson Kuang, Mikey Saugstad, Maryam Hosseini, Jon E. Froehlich

Poster Proceedings of ASSETS'22 | Acceptance Rate: 58.9% (43 / 73)

keywords: computer vision, urban informatics, deep learning, sidewalk assessment, sidewalk accessibility

PDF | doi | Citation | Project Sidewalk • Deep Learning for Sidewalk Assessment

Towards Global-Scale Crowd+AI Techniques to Map and Assess Sidewalks for People with Disabilities

Maryam Hosseini, Mikey Saugstad, Fabio Miranda, Andres Sevtsuk, Cláudio T. Silva, Jon E. Froehlich

CVPR2022 Workshop: Accessibility, Vision, and Autonomy (AVA)

keywords: accessible cities, urban informatics, urban accessibility, sidewalk assessment, sidewalk accessibility, sidewalk visualization

PDF | doi | Citation | Project Sidewalk • Deep Learning for Sidewalk Assessment

Deep Learning for Automatically Detecting Sidewalk Accessibility Problems Using Streetscape Imagery

Galen Weld, Esther Jang, Anthony Li, Aileen Zeng, Kurtis Heimerl, Jon E. Froehlich

Proceedings of ASSETS 2019 | Acceptance Rate: 25.9% (41 / 158) | Best Paper Award

keywords: mobility impairments, computer vision, urban informatics, deep learning, sidewalks, neural networks

PDF | doi | Citation | Code | Project Sidewalk • Deep Learning for Sidewalk Assessment