We propose an algorithm for the detection and reconstruction of plane surfaces using a new stereo approach dubbed SymStereo . SymStereo relies in symmetry analysis for re-covering the 3D curve where a virtual cut plane intersects the scene structure. The result is a profile cut that resembles the one that would be obtained by a Laser Range Finder (LRF). The article shows that the framework is particularly well suited for piecewise-planar reconstruction using only a pair of calibrated views. Since the intersection of two planes is always a line, the 3D space is sampled by a discrete set of virtual planes and the line segments in the profile cuts are extracted. The plane surfaces are determined by grouping co-planar lines using a straightforward RANSAC procedure in the dual Plücker space. We test the algorithm in estimating the relative pose of the stereo rig with respect to planes with different textures. The results are highly accurate and, more importantly, the approach succeeds in situations where current stereo methods fail due to low and/or repetitive texture. We also report experiments in wide-baseline stereo images of complex scenes with multiple planes partially occluded by non-planar objects.
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Plane Surface Detection and Reconstruction using Induced Stereo Symmetry
Semantic Scholar · Computer Science · 2011
Abstract
We propose an algorithm for the detection and reconstruction of plane surfaces using a new stereo approach dubbed SymStereo . SymStereo relies in symmetry analysis for re-covering the 3D curve where a virtual cut plane intersects the scene structure. The result is a profile cut that resembles the one that would be obtained by a Laser Range Finder (LRF). The article shows that the framework is particularly well suited for piecewise-planar reconstruction using only a pair of calibrated views. Since the intersection of two planes is always a line, the 3D space is sampled by a discrete set of virtual planes and the line segments in the profile cuts are extracted. The plane surfaces are determined by grouping co-planar lines using a straightforward RANSAC procedure in the dual Plücker space. We test the algorithm in estimating the relative pose of the stereo rig with respect to planes with different textures. The results are highly accurate and, more importantly, the approach succeeds in situations where current stereo methods fail due to low and/or repetitive texture. We also report experiments in wide-baseline stereo images of complex scenes with multiple planes partially occluded by non-planar objects.