Planar Urban Scene Reconstruction from Spherical Images using Facade Alignment
Kim, H and Hilton, A (2013) Planar Urban Scene Reconstruction from Spherical Images using Facade Alignment In: 11th IEEE IVMSP Workshop, 2013-06-10 - 2013-06-13, Seoul, South Korea.
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Abstract
We propose a plane-based urban scene reconstruction method using spherical stereo image pairs. We assume that the urban scene consists of axis-aligned approximately planar structures (Manhattan world). Captured spherical stereo images are converted into six central-point perspective images by cubic projection and facade alignment. Facade alignment automatically identifies the principal planes direction in the scene allowing the cubic projection to preserve the plane structure. Depth information is recovered by stereo matching between images and independent 3D rectangular planes are constructed by plane fitting aligned with the principal axes. Finally planar regions are refined by expanding, detecting intersections and cropping based on visibility. The reconstructed model efficiently represents the structure of the scene and texture mapping allows natural walk-through rendering.
Item Type: | Conference or Workshop Item (Conference Paper) | |||||||||
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Divisions : | Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing | |||||||||
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Date : | 10 June 2013 | |||||||||
Uncontrolled Keywords : | 3D Reconstruction, Spherical Imaging | |||||||||
Additional Information : | © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||
Depositing User : | Symplectic Elements | |||||||||
Date Deposited : | 07 Aug 2013 14:53 | |||||||||
Last Modified : | 31 Oct 2017 15:07 | |||||||||
URI: | http://epubs.surrey.ac.uk/id/eprint/788445 |
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