30 January 2012 Semiautomatic generation of semantic building models from image series
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Abstract
We present an approach to generate a 3D model of a building including semantic annotations from image series. In the recent years semantic based modeling, reconstruction of buildings and building recognition became more and more important. Semantic building models have more information than just the geometry, thus making them more suitable for recognition or simulation tasks. The time consuming generation of such models and annotations makes an automatism desirable. Therefore, we present a semiautomatic approach towards semantic model generation. This approach has been implemented as a plugin for the photostitching tool Hugin*. Our approach reduces the interaction with the system to a minimum. The resulting model contains semantic, geometric and appearance information and is represented in City Geography Markup Language (CityGML).
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Stefan Wirtz, Peter Decker, Dietrich Paulus, "Semiautomatic generation of semantic building models from image series", Proc. SPIE 8290, Three-Dimensional Image Processing (3DIP) and Applications II, 829019 (30 January 2012); doi: 10.1117/12.908489; https://doi.org/10.1117/12.908489
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