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RGB-D multi-view system calibration for full 3D scene reconstruction
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2014 (English)In: 2014 22nd International Conference on Pattern Recognition, IEEE conference proceedings, 2014, 2459-2464 p.Conference paper (Refereed)
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.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 2459-2464 p.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-163744DOI: 10.1109/ICPR.2014.425ISI: 000359818002097ScopusID: 2-s2.0-84919940968OAI: oai:DiVA.org:kth-163744DiVA: diva2:1082112
Conference
IEEE ICPR
Note

QC 20170322

Available from: 2017-03-15 Created: 2017-03-15 Last updated: 2017-03-22Bibliographically approved

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Ottersten, Björn
Signal Processing

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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Language
  • de-DE
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Output format
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