Indoor scene reconstruction using feature sensitive primitive extraction and graph-cut |
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Affiliation: | 1. School of Civil and Environmental Engineering, College of Engineering, Yonsei University, 134 Shinchondong, Seodaemungu, Seoul 120-749, Republic of Korea;2. School of Earth Sciences, The Ohio State University, 275 Mendenhall Laboratory, 125 South Oval Mall, Columbus, OH 43210, USA |
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Abstract: | We present a method for automatic reconstruction of permanent structures, such as walls, floors and ceilings, given a raw point cloud of an indoor scene. The main idea behind our approach is a graph-cut formulation to solve an inside/outside labeling of a space partitioning. We first partition the space in order to align the reconstructed models with permanent structures. The horizontal structures are located through analysis of the vertical point distribution, while vertical wall structures are detected through feature preserving multi-scale line fitting, followed by clustering in a Hough transform space. The final surface is extracted through a graph-cut formulation that trades faithfulness to measurement data for geometric complexity. A series of experiments show watertight surface meshes reconstructed from point clouds measured on multi-level buildings. |
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Keywords: | Indoor scenes 3D reconstruction Laser scanning Multi-scale line extraction Graph cut Energy minimization |
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