New Techniques for Automated Architectural Reconstruction from Photographs
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Partial and approximate symmetry detection for 3D geometry
ACM SIGGRAPH 2006 Papers
Detailed Real-Time Urban 3D Reconstruction from Video
International Journal of Computer Vision
Discovering structural regularity in 3D geometry
ACM SIGGRAPH 2008 papers
SmartBoxes for interactive urban reconstruction
ACM SIGGRAPH 2010 papers
Non-local scan consolidation for 3D urban scenes
ACM SIGGRAPH 2010 papers
Spatiotemporal Inpainting for Recovering Texture Maps of Occluded Building Facades
IEEE Transactions on Image Processing
A search-classify approach for cluttered indoor scene understanding
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
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Recently, researchers working in the fields of computer graphics and computer vision have shown tremendous interests in reconstructing urban scenes. For this task, the acquisition of the 3D point clouds is the first step, for which scans are usually widely utilized. Nevertheless, on seeing the potential drawbacks of scans, in this paper, we propose a novel urban scene reconstruction system based on the Multi-View Stereo (MVS). Given a set of calibrated photographs, we first generate point clouds using an existing MVS algorithm, and then reconstruct the sub-structures that often regularly repeat in urban buildings. Finally, we recover the entire architectural models through an automatic growing algorithm of the sub-structures in dominant directions. Experimental results on regular urban buildings show the practicality and high efficiency of the proposed reconstruction method.