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Methodology for 3D scene reconstruction from digital camera images. (English) Zbl 1260.62053

Balan, Vladimir (ed.) et al., Proceedings of the international conference on differential geometry and dynamical systems (DGDS-2011), Bucharest, Romania, October 6–9, 2011. Bucharest: Geometry Balkan Press. BSG Proceedings 19, 110-124 (2012).
Summary: Digital images provide today an important source of data that deserves a careful statistical analysis. This paper concerns methods for retrieval of 3D information, including shape and texture, from cheap digital camera imaging outputs. It includes a three step reconstruction of a 3D scene with texture. from arbitrary partial views, in absence of occlusions. In V. Patrangenaru and V.P. Patrangenaru, Mean shapes, image fusion and scene reconstruction. BSG Proc. 11, 230–242 (2004; Zbl 1061.62094)], a planar scene was reconstructed using image fusion, around representatives of sample mean projective shapes or sample mean affine shapes of landmark configurations shared by a number of partial views of the scene.
We first analyze the advantages and limitations of such a reconstruction of a close to planar remote scene from its partial aerial views, by specializing this algorithm to affine transformations. Furthermore, we combine a projective shape reconstruction of a finite 3D configuration from its uncalibrated camera views, as developed by V. Patrangenaru et al. [J. Multivariate Anal. 101, No. 1, 11–31 (2010; Zbl 1177.62059)], with a virtual reality modeling language (VRML) technique, to reconstruct projectively a 3D scene with texture from a pair of digital camera images, thus allowing a more detailed statistical analysis of the scene pictured. We give three such examples of 3D reconstructions.
For the entire collection see [Zbl 1247.00057].

MSC:

62H35 Image analysis in multivariate analysis
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
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