Title :
Hierarchical Co-Segmentation of Building Facades
Author :
Martinovic, Andelo ; Van Gool, Luc
Abstract :
We introduce a new system for automatic discovery of high-level structural representations of building facades. Under the assumption that each facade can be represented as a hierarchy of rectilinear subdivisions, our goal is to find the optimal direction of splitting, along with the number and positions of the split lines at each level of the tree. Unlike previous approaches, where each facade is analysed in isolation, we propose a joint analysis of a set of facade images. Initially, a co-segmentation approach is used to produce consistent decompositions across all facade images. Afterwards, a clustering step identifies semantically similar segments. Each cluster of similar segments is then used as the input for the joint segmentation in the next level of the hierarchy. We show that our approach produces consistent hierarchical segmentations on two different facade datasets. Furthermore, we argue that the discovered hierarchies capture essential structural information, which is demonstrated on the tasks of facade retrieval and virtual facade synthesis.
Keywords :
buildings (structures); image representation; image retrieval; image segmentation; pattern clustering; solid modelling; 3D city modeling; automatic high-level structural representation discovery; clustering step; facade datasets; facade retrieval; hierarchical building facade cosegmentation; rectilinear subdivision hierarchy; split lines; virtual facade synthesis; Image segmentation; Joints; Labeling; Optimization; Shape; Three-dimensional displays; Vectors; co-segmentation; facade analysis; facade parsing; hierarchical segmentation; hierarchy; urban modeling;
Conference_Titel :
3D Vision (3DV), 2014 2nd International Conference on
Conference_Location :
Tokyo
DOI :
10.1109/3DV.2014.26