Abstract
Abstract City models play a major role in urban planning and are indispensable in nowadays civil engineering. The ongoing automation of simulations and analyses demand for increasingly detailed models. Especially windows are of high interest for several tasks. As city models commonly lack any relevant details, these have to be complemented by information about windows from other data sources. In this paper, we propose a pipeline to detect windows in ground view facade images which are rectified before detection. A postprocessing is applied to refine the detections made by a soft cascaded classifier and infer further windows. In experiments we compare our approach to previous work and evaluate the processing steps of our pipeline. Moreover, we show that our entire system yields a detection rate of 95% and a precision of 97% which is satisfying for a proper advancement of existing 3D city models.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
