迈向印度的人机可及性映射：在昌迪加尔的VLM引导标注与POI中心分析
Towards Human-AI Accessibility Mapping in India: VLM-Guided Annotations and POI-Centric Analysis in Chandigarh
AI总结：
本文提出在印度昌迪加尔部署Project Sidewalk工具，通过VLM引导标注和POI中心分析，评估了城市无障碍性改进的潜力。
摘要：
Project Sidewalk是一个基于网络的平台，通过使用谷歌街景虚拟行走来实现城市级别的无障碍性众包。该工具已在世界各地的40个城市中使用，包括美国、墨西哥、智利和欧洲。在本文中，我们描述了适应努力，以在昌迪加尔印度部署，包括修改注释类型、提供示例以及整合基于VLM的使命指导，该指导根据街道场景和元数据分析进行调整。我们的评估显示，使用AI使命指导的平均得分为4.66。利用这种适应后的Project Sidewalk工具，我们对昌迪加尔的三个区域进行了以兴趣点（POI）为中心的无障碍性分析，这些区域的土地利用差异很大，包括住宅、商业和机构，覆盖约40公里的人行道。在对40公里道路进行审计的三个区域和约230个POI中，我们确定了1,644个2,913个地点，其中基础设施改进可以提高可及性。
英文摘要：
Project Sidewalk is a web-based platform that enables crowdsourcing accessibility of sidewalks at city-scale by virtually walking through city streets using Google Street View. The tool has been used in 40 cities across the world, including the US, Mexico, Chile, and Europe. In this paper, we describe adaptation efforts to enable deployment in Chandigarh, India, including modifying annotation types, provided examples, and integrating VLM-based mission guidance, which adapts instructions based on a street scene and metadata analysis. Our evaluation with 3 annotators indicates the utility of AI-mission guidance with an average score of 4.66. Using this adapted Project Sidewalk tool, we conduct a Points of Interest (POI)-centric accessibility analysis for three sectors in Chandigarh with very different land uses, residential, commercial and institutional covering about 40 km of sidewalks. Across 40 km of roads audited in three sectors and around 230 POIs, we identified 1,644 of 2,913 locations where infrastructure improvements could enhance accessibility.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
