Robust piecewise-planar 3D reconstruction and completion from large-scale unstructured point data

Anne-Laure Chauve, Patrick Labatut, Jean-Philippe Pons
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
In this paper, we present a novel method, the first to date to our knowledge, which is capable of directly and automatically producing a concise and idealized 3D representation from unstructured point data of complex cluttered real-world scenes, with a high level of noise and a significant proportion of outliers, such as those obtained from passive stereo. Our algorithm can digest millions of input points into an optimized lightweight watertight polygonal mesh free of self-intersection, that
more » ... tersection, that preserves the structural components of the scene at a user-defined scale, and completes missing scene parts in a plausible manner. To achieve this, our algorithm incorporates priors on urban and architectural scenes, notably the prevalence of vertical structures and orthogonal intersections. A major contribution of our work is an adaptive decomposition of 3D space induced by planar primitives, namely a polyhedral cell complex. We experimentally validate our approach on several challenging noisy point clouds of urban and architectural scenes.
doi:10.1109/cvpr.2010.5539824 dblp:conf/cvpr/ChauveLP10 fatcat:xvbs7omynve4halo4k65r4qhvy