DocumentCode :
178247
Title :
RGB-D Multi-view System Calibration for Full 3D Scene Reconstruction
Author :
Afzal, H. ; Aouada, D. ; Foni, D. ; Mirbach, B. ; Ottersten, B.
Author_Institution :
Interdiscipl. Centre for Security, Reliability & Trust Univ. of Luxembourg, Luxembourg
fYear :
2014
fDate :
24-28 Aug. 2014
Firstpage :
2459
Lastpage :
2464
Abstract :
One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We propose BAICP+ which combines Bundle Adjustment (BA) and Iterative Closest Point (ICP) algorithms to take into account both 2D visual and 3D shape information in one minimization formulation to estimate relative pose parameters of each camera. BAICP+ is generic enough to take different types of visual features into account and can be easily adapted to varying quality of 2D and 3D data. We perform experiments on real and simulated data. Results show that with the right weighting factor BAICP+ has an optimal performance when compared to BA and ICP used independently or sequentially.
Keywords :
calibration; cameras; image colour analysis; image reconstruction; minimisation; pose estimation; 2D visual information; 3D scene reconstruction; 3D shape information; BA algorithm; BAICP+; ICP algorithm; RGB-D camera based multiview system; RGB-D multiview system calibration; bundle adjustment algorithm; camera relative pose estimation; iterative closest point algorithm; minimization formulation; Barium; Calibration; Cameras; Feature extraction; Iterative closest point algorithm; Three-dimensional displays; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location :
Stockholm
ISSN :
1051-4651
Type :
conf
DOI :
10.1109/ICPR.2014.425
Filename :
6977138
Link To Document :
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