Large Scale Architectural Asset Extraction from Panoramic Imagery

  • Peihao Zhu

Student thesis: Master's Thesis


We present a system to extract architectural assets from large-scale collections of panoramic imagery. We automatically rectify and crop parts of the panoramic image that contain dominant planes, and then use object detection to extract assets such as facades and windows. We also provide various tools to identify attributes of the assets to determine the asset quality and index the assets for search. In addition, we propose a UI to visualize and query assets. Finally, we present applications for urban modeling and texture synthesis.
Date of Award2020
Original languageEnglish (US)
Awarding Institution
  • Computer, Electrical and Mathematical Sciences and Engineering
SupervisorPeter Wonka (Supervisor)

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