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3D modelling of static environments using multiple spherical stereo

3D modelling of static environments using multiple spherical stereo
3D modelling of static environments using multiple spherical stereo
We propose a 3D modelling method from multiple pairs of spherical stereo images. A static environment is captured as a vertical stereo pair with a rotating line scan camera at multiple locations and depth fields are extracted for each pair using spherical stereo geometry. We propose a new PDE-based stereo matching method which handles occlusion and over-segmentation problem in highly textured regions. In order to avoid cumbersome camera calibration steps, we extract a 3D rigid transform using feature matching between views and fuse all models into one complete mesh. A reliable surface selection algorithm for overlapped surfaces is proposed for merging multiple meshes in order to keep surface details while removing outliers. The performances of the proposed algorithms are evaluated against ground-truth from LIDAR scans. © 2012 Springer-Verlag.
3D modelling, Camera calibration, Disparity estimations, Environment modelling, Feature matching, Line-scan cameras, Multiple pairs, Over segmentation, Spherical stereo, Static environment, Stereo matching method, Stereo pair, Stereo reconstruction, Surface details, Surface selection, Textured regions, Algorithms, Cameras, Computer vision, Face recognition, Optical radar, Spheres
0302-9743
169-183
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db

Kim, H. and Hilton, Adrian (2012) 3D modelling of static environments using multiple spherical stereo. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6554 LNCS (PART 2), 169-183. (doi:10.1007/978-3-642-35740-4_14).

Record type: Article

Abstract

We propose a 3D modelling method from multiple pairs of spherical stereo images. A static environment is captured as a vertical stereo pair with a rotating line scan camera at multiple locations and depth fields are extracted for each pair using spherical stereo geometry. We propose a new PDE-based stereo matching method which handles occlusion and over-segmentation problem in highly textured regions. In order to avoid cumbersome camera calibration steps, we extract a 3D rigid transform using feature matching between views and fuse all models into one complete mesh. A reliable surface selection algorithm for overlapped surfaces is proposed for merging multiple meshes in order to keep surface details while removing outliers. The performances of the proposed algorithms are evaluated against ground-truth from LIDAR scans. © 2012 Springer-Verlag.

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More information

Published date: 2012
Additional Information: cited By 0
Keywords: 3D modelling, Camera calibration, Disparity estimations, Environment modelling, Feature matching, Line-scan cameras, Multiple pairs, Over segmentation, Spherical stereo, Static environment, Stereo matching method, Stereo pair, Stereo reconstruction, Surface details, Surface selection, Textured regions, Algorithms, Cameras, Computer vision, Face recognition, Optical radar, Spheres

Identifiers

Local EPrints ID: 440579
URI: http://eprints.soton.ac.uk/id/eprint/440579
ISSN: 0302-9743
PURE UUID: aed04e93-d58e-419c-940b-e5034dba94e7
ORCID for H. Kim: ORCID iD orcid.org/0000-0003-4907-0491

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Date deposited: 07 May 2020 16:37
Last modified: 23 May 2020 00:47

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