Incremental Line-based 3D Reconstruction using Geometric Constraints
Author(s) -
Manuel Höfer,
Andreas Wendel,
Horst Bischof
Publication year - 2013
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.27.92
Subject(s) - computer science , point cloud , artificial intelligence , 3d reconstruction , computer vision , representation (politics) , matching (statistics) , line (geometry) , point (geometry) , feature (linguistics) , solid modeling , line segment , pattern recognition (psychology) , algorithm , mathematics , geometry , linguistics , statistics , philosophy , politics , political science , law
Generating accurate 3D models for man-made environments can be a challenging task due to the presence of texture-less objects or wiry structures. Since traditional point-based 3D reconstruction approaches may fail to integrate these structures into the resulting point cloud, a different feature representation is necessary. We present a novel approach which uses point features for camera estimation and additional line segments for 3D reconstruction. To avoid appearance-based line matching, we use purely geometric constraints for hypothesis generation and verification. Therefore, the proposed method is able to reconstruct both wiry structures as well as solid objects. The algorithm is designed to generate incremental results using online Structure-from-Motion and linebased 3D modelling in parallel. We show that the proposed method outperforms previous descriptor-less line matching approaches in terms of run-time while delivering accurate
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