论文标题
迈向全球规模的人群+AI技术，以绘制和评估残疾人的人行道
Towards Global-Scale Crowd+AI Techniques to Map and Assess Sidewalks for People with Disabilities
论文作者
论文摘要
在世界各地人行道的位置，状况和可及性上缺乏数据，这不仅会影响人们的旅行何处和方式，而且从根本上限制了交互式映射工具和城市分析。在本文中，我们使用层次多尺度注意模型从卫星图像中构建了半自动性的初步工作，从卫星图像中构建了人行道网络拓扑模型，从而使用基于学习的基于学习的语义细分从街道级图像中推断出表面材料，并使用CROVS+AI评估人行道的语义条件和可访问性。我们呼吁创建一个标有卫星和街景场景的数据库，以供人行道和人行道可及性问题以及标准化的基准测试。
There is a lack of data on the location, condition, and accessibility of sidewalks across the world, which not only impacts where and how people travel but also fundamentally limits interactive mapping tools and urban analytics. In this paper, we describe initial work in semi-automatically building a sidewalk network topology from satellite imagery using hierarchical multi-scale attention models, inferring surface materials from street-level images using active learning-based semantic segmentation, and assessing sidewalk condition and accessibility features using Crowd+AI. We close with a call to create a database of labeled satellite and streetscape scenes for sidewalks and sidewalk accessibility issues along with standardized benchmarks.
