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A FORMULATION FOR UNSUPERVISED HIERARCHICAL SEGMENTATION OF FACADE IMAGES WITH PERIODIC MODELS

International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences(2010)

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摘要
We introduce an unsupervised segmentation method to build a hierarchical representation of a building facade from a single calibrated street level image. The process recursively splits horizontally or vertically the rectified image along dominant alignments until the radiometric content of the region hypothesis corresponds to a given model. This paper propose two main novelties: first we describe an advanced split energy formulation to separate dominant alignments breaks. Then we introduce a model that express periodicity in facade texture. This segmentation could be an interesting tool for facade modeling and is in particular well suited for facade texture compression.
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关键词
street level imagery,facade reconstruction,unsupervised hierarchical segmentation,gradient accumulation,recursive split,model matching,periodicity detection
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