A FORMULATION FOR UNSUPERVISED HIERARCHICAL SEGMENTATION OF FACADE IMAGES WITH PERIODIC MODELS
International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences(2010)
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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