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The SemanticCity project aims to automate the processing of raw 3D city scan data to create structured models for applications like augmented reality and urban planning. This will significantly reduce the time and cost associated with semantic annotation of large datasets.
Many massive data sources now exist for large scale 3D measurements in the form of raw pointclouds or polygonal soups.
Such raw data, however, have to be cleaned, consolidated, and semantically annotated before they can be consumed by downstream applications (e.g., augmented reality, procedural modeling, energy simulation, etc.).
This manual step is a major processing bottleneck resulting in significant economic and efficiency costs.
For example, state-of-the-art workflows in location-based serv…
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