RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction |
| Type de publication | Conference Paper |
| Year of Publication | 2014 |
| Auteurs | Afzal H, Aouada D, Fofi D, Mirbach B, Ottersten B |
| Conference Name | 2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) |
| Publisher | IEEE Comp Soc; IAPR; Linkopings Univ; Lunds Univ; Uppsala Univ; e Sci Collaborat; Swedish Soc Automated Image Anal; Stockhoms Stad; Swedish e Sci Res Ctr; SICK; Autoliv; IBM Res; Int Journal Automat & Comp |
| Conference Location | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA |
| ISBN Number | 978-1-4799-5208-3 |
| Résumé | 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. |
| DOI | 10.1109/ICPR.2014.425 |