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Soft Computing

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05.12.2017 | Foundations

Multi-view 3D reconstruction and modeling of the unknown 3D scenes using genetic algorithms

verfasst von: Mostafa Merras, Abderrahim Saaidi, Nabil El Akkad, Khalid Satori

Erschienen in: Soft Computing | Ausgabe 19/2018

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Abstract

This paper presents a complete pipeline of the reconstruction and the modeling of the unknown complex 3D scenes from a sequence of unconstrained images. The proposed system is based on the formulation of a nonlinear cost function by determining the relationship between 2D points of the images and the cameras parameters; the optimization of this function by a genetic algorithm makes finding the optimal cameras parameters. The determination of these parameters allows thereafter to estimate the 3D points of the observed scene. Then, the mesh of the 3D points is achieved by 3D Crust algorithm and the texture mapping is performed by multiple dependent viewpoints. Extensive experiments on synthetic and real data are performed to validate the proposed approach, and the results indicate that our system is robust and can achieve a very satisfactory reconstruction quality.

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Titel: Multi-view 3D reconstruction and modeling of the unknown 3D scenes using genetic algorithms
verfasst von: Mostafa Merras
Abderrahim Saaidi
Nabil El Akkad
Khalid Satori
Publikationsdatum: 05.12.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 19/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-017-2966-z

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