Omnidirectional texturing based on robust 3D registration through Euclidean reconstruction from two spherical images

We propose a semi-automatic omnidirectional texturing method that maps a spherical image onto a dense 3D model obtained by a range sensor. For accurate texturing, accurate estimation of the extrinsic parameters is inevitable. In order to estimate these parameters, we propose a robust 3D registration...

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Bibliographic Details
Published in:Computer vision and image understanding 2010-04, Vol.114 (4), p.491-499
Main Authors: Banno, Atsuhiko, Ikeuchi, Katsushi
Format: Article
Language:English
Subjects:
3D registration
Applied sciences
Artificial intelligence
C (programming language)
Computer science
control theory
systems
Error analysis
Exact sciences and technology
Mathematical models
Omnidirectional image rectification
Omnidirectional image stereo
Pattern recognition. Digital image processing. Computational geometry
Texturing
Three dimensional
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Summary:We propose a semi-automatic omnidirectional texturing method that maps a spherical image onto a dense 3D model obtained by a range sensor. For accurate texturing, accurate estimation of the extrinsic parameters is inevitable. In order to estimate these parameters, we propose a robust 3D registration-based method between a dense range data set and a sparse spherical image stereo data set. For measuring the distances between the two data sets, we introduce generalized distances taking account of 3D error distributions of the stereo data. To reconstruct 3D models by images, we use two spherical images taken at arbitrary positions in arbitrary poses. Then, we propose a novel rectification method for spherical images that is derived from E matrix and facilitates the estimation of the disparities. The experimental results show that the proposed method can map the spherical image onto the dense 3D models effectively and accurately.
ISSN:1077-3142
1090-235X
DOI:10.1016/j.cviu.2009.12.005