PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

3D from Line Segments in Two Poorly-Textured, Uncalibrated Images
Herbert Bay, Andreas Ess, Alexander Neubeck, Luc Van Gool and Luc Van Gool
In: Proceedings of the Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT), 14-16 June, 2006, Chapel Hill, USA.


This paper addresses the problem of camera selfcalibration, bundle adjustment and 3D reconstruction from line segments in two images of poorly-textured indoor scenes. First, we generate line segment correspondences, using an extended version of our previously proposed matching scheme. The first main contribution is a new method to identify polyhedral junctions resulting from the intersections of the line segments. At the same time, the images are segmented into planar polygons. This is done using an algorithm based on a Binary Space Partitioning (BSP) tree. The junctions are matched end points of the detected line segments and hence can be used to obtain the epipolar geometry. The essential matrix is considered for metric camera calibration. For better stability, the second main contribution consists in a bundle adjustment on the line segments and the camera parameters that reduces the number of unknowns by a maximum flow algorithm. Finally, a piecewise-planar 3D reconstruction is computed based on the segmentation of the BSP tree. The system’s performance is tested on some challenging examples.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:3638
Deposited By:Luc Van Gool
Deposited On:14 February 2008