Reference : RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/17042
RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction
English
Afzal, Hassan mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Aouada, Djamila mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Fofi, David mailto [Universite de Bourgogne]
Mirbach, Bruno mailto []
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
2014
22nd International Conference on Pattern Recognition (ICPR'14)
Yes
International
22nd International Conference on Pattern Recognition
from 24-08-2014 to 28-08-2014
[en] 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.
Fonds National de la Recherche - FnR
http://hdl.handle.net/10993/17042

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