RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction

AFZAL, Hassan; AOUADA, Djamila; Fofi, David; Mirbach, Bruno; OTTERSTEN, Björn

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RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction

AFZAL, Hassan; AOUADA, Djamila; Fofi, David et al.

2014 • In 22nd International Conference on Pattern Recognition (ICPR'14)

Peer reviewed

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https://hdl.handle.net/10993/17042

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Abstract :

[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.

Disciplines :

Computer science

Author, co-author :

AFZAL, Hassan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

AOUADA, Djamila ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Fofi, David; Universite de Bourgogne

Mirbach, Bruno

OTTERSTEN, Björn ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

Language :

English

Title :

RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction

Publication date :

2014

Event name :

22nd International Conference on Pattern Recognition

Event date :

from 24-08-2014 to 28-08-2014

Audience :

International

Main work title :

22nd International Conference on Pattern Recognition (ICPR'14)

Peer reviewed :

Peer reviewed

Name of the research project :

R-AGR-0686-1 > C11/IS/1204105 : FAVE > 01/01/2012 - 31/12/2014 > OTTERSTEN Björn

Funders :

FNR - Fonds National de la Recherche

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since 24 June 2014

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