Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
An interactive approach to semantic modeling of indoor scenes with an RGBD camera
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Acquiring 3D indoor environments with variability and repetition
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Reconstructing the world's museums
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
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We present a method for automatic reconstruction of permanent structures of indoor scenes, such as walls, floors and ceilings, from raw point clouds acquired by laser scanners. Our approach employs graph-cut to solve an inside/outside labeling of a space decomposition. To allow for an accurate reconstruction the space decomposition is aligned with permanent structures. A Hough Transform is applied for extracting the wall directions while allowing a flexible reconstruction of scenes. The graph-cut formulation takes into account data consistency through an inside/outside prediction for the cells of the space decomposition by stochastic ray casting, while favoring low geometric complexity of the model. Our experiments produces watertight reconstructed models of multi-level buildings and complex scenes.