Use of generalised Procrustes analysis for the photogrammetric block adjustment by independent models

Crosilla, Fabio; Beinat, Alberto

doi:10.1016/s0924-2716(02)00043-6

Cited by 59 publications

(40 citation statements)

References 7 publications

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“…In the application of the original Procrustes method, the geodetic pioneer was F. Crosilla, while for photogrammetry they were F. A. Beinat (e.g., Crosilla, 1983a, b, 2003;Crosilla and Beinat, 2002).…”

Section: Procrustes Problemsmentioning

confidence: 99%

Extension of the ABC-Procrustes algorithm for 3D affine coordinate transformation

et al. 2010

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The Procrustes method is a very effective method for determining the Helmert's datum transformation parameters since it requires neither initial starting values nor iteration. Due to these attractive attributes, the ABCProcrustes algorithm is extended to solve the 3D affine transformation problem where scale factors are different in the 3 principal directions X, Y, Z . In this study, it is shown that such a direct extension is restricted to cases of mild anisotropy in scaling. For strong anisotropy, however, the procedure fails. The PZ-method is proposed as an extension of the ABC algorithm for this special case. The procedures are applied to determine transformation parameters for; (i) transforming the Australian Geodetic Datum (AGD 84) to the Geocentric Datum Australia (GDA 94), i.e., mild anisotropy and (ii) synthetic data for strong anisotropy. The results indicate that the PZalgorithm leads to a local multivariate minimization as opposed to the ABC-algorithm, thus requiring slightly longer computational time. However, the ABC-method is found to be useful for computing proper initial values for the PZ-method, thereby increasing its efficiency.

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Section: Procrustes Problemsmentioning

confidence: 99%

Extension of the ABC-Procrustes algorithm for 3D affine coordinate transformation

et al. 2010

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“…sn. In the bundle block adjustment problem it is required to simultaneously find the image exterior orientation parameters and the tie-points 3-D coordinates that minimize a geometric error, without introducing intermediate models, as opposed to the block adjustment by independent models (Crosilla and Beinat, 2002). We review here the Procrustean solution to the free-network bundle block adjustment problem presented by (Fusiello and Crosilla, 2015).…”

Section: Problem Formulationmentioning

confidence: 99%

“…In the field of photogrammetry, (Crosilla and Beinat, 2002) applied the GPA to the solution of block adjustment by independent models, while (Garro et al, 2012) applied OPA (with anisotropic row-scaling) to solve the exterior orientation problem. In a recent paper (Fusiello and Crosilla, 2015) the Procrustean solution of the classical bundle block adjustment has been described.…”

Section: Introductionmentioning

confidence: 99%

Fast and Resistant Procrustean Bundle Adjustment

Fusiello

Crosilla

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In a recent paper (Fusiello and Crosilla, 2015) a Procrustean formulation of the bundle block adjustment has been presented, with a solution based on alternating least squares. This paper improves on it in two respects: it introduces a faster iterative scheme that minimizes the same cost function, thereby achieving the same accuracy, and makes the method resistant to rogue measures through iteratively reweighted least-squares. Empirical results confirm the effectiveness of these enhancements.

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“…(Crosilla and Beinat, 2002)), where first stereo-models are built and co-registered, structure-and-motion methods, such as bundle block adjustment (e.g. (Triggs et al, 2000)), resection-intersection methods (Brown andLowe, 2005, Snavely et al, 2006), hierarchical methods (Gherardi et al, 2010, Ni andDellaert, 2012)), where "structure" and "motion" are solved simultaneously, and -more recently -motion-first methods (Govindu, 2001, Martinec and Pajdla, 2007, Kahl and Hartley, 2008, Enqvist et al, 2011, ArieNachimson et al, 2012, Moulon et al, 2013) that first solve for the "motion" and then recover the "structure".…”

Section: Introductionmentioning

confidence: 99%

Robust Global Motion Estimation with Matrix Completion

Arrigoni

Rossi

Malapelle

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In this paper we address the problem of estimating the attitudes and positions of a set of cameras in an external coordinate system. Starting from a conventional global structure-from-motion pipeline, we present some substantial advances. In order to detect outlier relative rotations extracted from pairs of views, we improve a state-of-the-art algorithm based on cycle consistency, by introducing cycle bases. We estimate the angular attitudes of the cameras by proposing a novel gradient descent algorithm based on low-rank matrix completion, that naturally copes with the case of missing data. As for position recovery, we analyze an existing technique from a theoretical point of view, providing some insights on the conditions that guarantee solvability. We provide experimental results on both synthetic and real image sequences for which ground truth calibration is provided.

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Use of generalised Procrustes analysis for the photogrammetric block adjustment by independent models

Cited by 59 publications

References 7 publications

Extension of the ABC-Procrustes algorithm for 3D affine coordinate transformation

Extension of the ABC-Procrustes algorithm for 3D affine coordinate transformation

Fast and Resistant Procrustean Bundle Adjustment

Robust Global Motion Estimation with Matrix Completion

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