BigSUR: Large-scale Structured Urban Reconstruction

T. Kelly, J. Femiani, P. Wonka, N. Mitra
Siggraph Asia, ACM Transactions on Graphics, vol. 36, no. 6, article 204, (2017)

BigSUR: Large-scale Structured Urban Reconstruction

Keywords

Urban modeling, Structure, Reconstruction, Facade parsing and element classification, Procedural modeling

Abstract

The creation of high-quality semantically parsed 3D models for dense metropolitan areas is a fundamental urban modeling problem. Although recent advances in acquisition techniques and processing algorithms have resulted in large-scale imagery or 3D polygonal reconstructions, such data-sources are typically noisy, and incomplete, with no semantic structure. In this paper, we present an automatic data fusion technique that produces high-quality structured models of city blocks. From coarse polygonal meshes, street-level imagery, and GIS footprints, we formulate a binary integer program that globally balances sources of error to produce semantically parsed mass models with associated façade elements. We demonstrate our system on four city regions of varying complexity; our examples typically contain densely built urban blocks spanning hundreds of buildings. In our largest example, we produce a structured model of 37 city blocks spanning a total of 1,011 buildings at a scale and quality previously impossible to achieve automatically.

Code

DOI: 10.1145/3130800.3130823

Sources

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