Sidewalk Material

Research on sidewalk materials focuses on developing efficient and accurate methods for assessing sidewalk conditions and accessibility, primarily using computer vision and machine learning techniques. Current efforts leverage diverse data sources, including street-level imagery, 3D point clouds, and satellite imagery, employing models like semantic segmentation and hierarchical multi-scale attention networks to analyze sidewalk width, material composition, and the presence of obstacles. This research is crucial for improving urban planning, enhancing accessibility for people with disabilities, and supporting more sustainable city infrastructure management by providing large-scale, detailed data on sidewalk characteristics.