Rectilinear Parsing Of Architecture In Urban Environment
2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)(2010)
摘要
We propose an approach that parses registered images captured at ground level into architectural units for large-scale city modeling. Each parsed unit has a regularized shape, which can be used for further modeling purposes. In our approach, we first parse the environment into buildings, the ground, and the sky using a joint 2D-3D segmentation method. Then, we partition buildings into individual facades. The partition problem is formulated as a dynamic programming optimization for a sequence of natural vertical separating lines. Each facade is regularized by a floor line and a roof line. The floor line is the intersection line of the vertical plane of buildings and the horizontal plane of the ground. The roof line links edge points of roof region. The parsed results provide a first geometric approximation to the city environment, and can be further analyzed if necessary. The approach is demonstrated and validated on several large-scale city datasets.
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关键词
image registration,architecture,computational geometry,dynamic programming,image reconstruction,cartography,layout,approximation theory,image segmentation,earth,shape
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