From Detailed Digital Surface Models to City Models Using Constrained Simplification
نویسندگان
چکیده
We present a method to simplify high-detail full-featured digital surface models (DSM) of cities (i.e. containing the heights of trees, cars, buildings, etc.) geometrically in such a way that all relevant features are preserved, whereas noise and superfluous details collapse. The relevance of features is automatically evaluated using a semantically motivated shape detection and serves as constraint during the simplification. Our results show that we are able to preserve fine details of complex roof structures while all irrelevant features are effectively removed. Thus, we achieve an excellent abstraction of the city data without any interaction of the user, which is not only beneficial for visualization, but could also be used for GIS related applications.
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