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Fast and accurate refinement method for 3D reconstruction from stereo spherical images

Fast and accurate refinement method for 3D reconstruction from stereo spherical images
Fast and accurate refinement method for 3D reconstruction from stereo spherical images
Realistic 3D models of the environment are beneficial in many fields, from natural or man-made structure inspection and volumetric analysis, to movie-making, in particular, special effects integration to natural scenes. Spherical cameras are becoming popular in environment modelling because they capture the full surrounding scene visible from the camera location as a consistent seamless image at once. In this paper, we propose a novel pipeline to obtain fast and accurate 3D reconstructions from spherical images. In order to have a better estimation of the structure, the system integrates a joint camera pose and structure refinement step. This strategy proves to be much faster, yet equally accurate, when compared to the conventional method, registration of a dense point cloud via iterative closest point (ICP). Both methods require an initial estimate for successful convergence. The initial positions of the 3D points are obtained from stereo processing of pair of spherical images with known baseline. The initial positions of the cameras are obtained from a robust wide-baseline matching procedure. The performance and accuracy of the 3D reconstruction pipeline is analysed through extensive tests on several indoor and outdoor datasets.
Cameras, Computer vision, Image processing, Image reconstruction, Iterative methods, Pipelines, Spheres, Volumetric analysis, 3D reconstruction, Environment modelling, Iterative closest point, Optimisations, SLAM, Spherical images, Structure refinements, Wide-baseline matching, Stereo image processing
575-583
Solony, M.
6b39dabc-7e9a-49d8-99a4-b32b0f62c5c6
Imre, E.
d5e10a85-873f-4e03-80b4-d6c3f4c6ca3d
Ila, V.
699c4e52-9c1d-4bf2-b64d-dae91e5046df
Polok, L.
76afc50a-4c97-4449-8d89-15b88df23a1c
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Zemcik, P.
69e3c0fc-c6b6-4bd6-bd73-3bf7f83d64d9
Solony, M.
6b39dabc-7e9a-49d8-99a4-b32b0f62c5c6
Imre, E.
d5e10a85-873f-4e03-80b4-d6c3f4c6ca3d
Ila, V.
699c4e52-9c1d-4bf2-b64d-dae91e5046df
Polok, L.
76afc50a-4c97-4449-8d89-15b88df23a1c
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Zemcik, P.
69e3c0fc-c6b6-4bd6-bd73-3bf7f83d64d9

Solony, M., Imre, E., Ila, V., Polok, L., Kim, H. and Zemcik, P. (2015) Fast and accurate refinement method for 3D reconstruction from stereo spherical images. 10th International Conference on Computer Vision Theory and Applications, Germany. 11 - 14 Mar 2015. pp. 575-583 .

Record type: Conference or Workshop Item (Paper)

Abstract

Realistic 3D models of the environment are beneficial in many fields, from natural or man-made structure inspection and volumetric analysis, to movie-making, in particular, special effects integration to natural scenes. Spherical cameras are becoming popular in environment modelling because they capture the full surrounding scene visible from the camera location as a consistent seamless image at once. In this paper, we propose a novel pipeline to obtain fast and accurate 3D reconstructions from spherical images. In order to have a better estimation of the structure, the system integrates a joint camera pose and structure refinement step. This strategy proves to be much faster, yet equally accurate, when compared to the conventional method, registration of a dense point cloud via iterative closest point (ICP). Both methods require an initial estimate for successful convergence. The initial positions of the 3D points are obtained from stereo processing of pair of spherical images with known baseline. The initial positions of the cameras are obtained from a robust wide-baseline matching procedure. The performance and accuracy of the 3D reconstruction pipeline is analysed through extensive tests on several indoor and outdoor datasets.

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More information

e-pub ahead of print date: 11 March 2015
Additional Information: cited By 1
Venue - Dates: 10th International Conference on Computer Vision Theory and Applications, Germany, 2015-03-11 - 2015-03-14
Keywords: Cameras, Computer vision, Image processing, Image reconstruction, Iterative methods, Pipelines, Spheres, Volumetric analysis, 3D reconstruction, Environment modelling, Iterative closest point, Optimisations, SLAM, Spherical images, Structure refinements, Wide-baseline matching, Stereo image processing

Identifiers

Local EPrints ID: 440586
URI: http://eprints.soton.ac.uk/id/eprint/440586
PURE UUID: 2960d9a5-185a-499e-9beb-075fa6fa0a44
ORCID for H. Kim: ORCID iD orcid.org/0000-0003-4907-0491

Catalogue record

Date deposited: 07 May 2020 16:38
Last modified: 23 May 2020 00:47

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