A Case-based Search Engine for Mapping Urban Patterns and Cases Integrating Street View Imagery

Abstract

This conference presentation is about a case-based search engine that has been developed to collect urban semantic, spatial, and image data, to extract geometry and image features, and with unsupervised learning, the urban patterns can be elucidated. The engine provides users with a city map with general urban patterns and various related urban cases, and can help architects and urban designers with decision-making. Presenter will be using Nanjing as a case study to demonstrate the engine’s applications.