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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 8/2013

01.11.2013 | Original Paper

Multi-view dense 3D modelling of untextured objects from a moving projector-cameras system

verfasst von: Jacques Harvent, Benjamin Coudrin, Ludovic Brèthes, Jean-José Orteu, Michel Devy

Erschienen in: Machine Vision and Applications | Ausgabe 8/2013

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Abstract

Structured light methods achieve 3D modelling by observing with a camera system, a known pattern projected on the scene. The main drawback of single projection structured light methods is that moving the projector changes significatively the appearance of the scene at every acquisition time. Classical multi-view stereovision approaches based on the appearance matching are then not useable. The presented work is based on a two-cameras and one single slide projector system embedded in a hand-held device for industrial applications (reverse engineering, dimensional control, etc). We propose a method to achieve multi-view modelling for camera pose and surface reconstruction estimation in a joint process. The proposed method is based on the extension of a stereo-correlation criterion. Acquisitions are linked through a generalized expression of local homographies. The constraints brought by this formulation allow an accurate estimation of the modelling parameters for dense reconstruction of the scene and improve the result when dealing with detailed or sharp objects, compared to pairwise stereovision methods.
Vorheriger Artikel Efficient segmentation of leaves in semi-controlled conditions
Nächster Artikel A machine vision system to estimate cotton fiber maturity from longitudinal view using a transfer learning approach

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Fußnoten
1
The poses are considered optimal from our method point of view, that is to say that they are fully observed and that no better convergence can be achieved from adding keypoints.
 
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Metadaten
Titel
Multi-view dense 3D modelling of untextured objects from a moving projector-cameras system
verfasst von
Jacques Harvent
Benjamin Coudrin
Ludovic Brèthes
Jean-José Orteu
Michel Devy
Publikationsdatum
01.11.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 8/2013
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-013-0495-z

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