Fast total least squares vectorization

Jelinek, Ales; Žalud, Luděk; Jílek, Tomáš

doi:10.1007/s11554-016-0562-6

Cited by 9 publications

(7 citation statements)

References 38 publications

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“…All of these examples prove that geometrical primitives have their benefits. In [23], we have shown, that proper approximation using a more complex geometric primitive can reliably reduce the noise inherently present in the point cloud, which disproves the criticism in [18]. In combination with the general tendency towards object-oriented mapping in robotics [3], the complex object registration seems to be a viable research direction.…”

Section: Geometrical Primitives In the Registration Processmentioning

confidence: 81%

“…Number of points per scan and Gaussian noise can be set individually for every measurement. Point-like data are processed using the total least squares vectorization algorithm [23], providing a set of line segments to be registered with the map. Exactly given poses of the scanner serve for the verification of quality of the registration process.…”

Section: Experimental Verificationmentioning

confidence: 99%

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On registration of vector maps with known correspondences

Jelinek

2018

2018 Elektro

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Data association and registration is an important and actively researched topic in robotics. This paper deals with registration of two sets of line segments, which is especially useful in mapping applications. Our method is non-iterative, finding an optimal transformation in a single step, in a time proportional only to a number of the corresponding line segments. The procedure also provides diagnostic measures of reliability of the computation and of similarity of the data sets being registered. At this point, the method presumes known correspondences, which is limiting, but the discussion, in the end, reveals some possibilities to overcome this issue. Practical properties are demonstrated on a typical task of localization of a robot with a known map.

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Section: Geometrical Primitives In the Registration Processmentioning

confidence: 81%

Section: Experimental Verificationmentioning

confidence: 99%

On registration of vector maps with known correspondences

Jelinek

2018

2018 Elektro

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“…Traditional point-eliminating approaches are covered and Douglas-Peucker [19] algorithm), but the main focus is on total least squares (TLS) fitting. There is an implementation of the fast total least squares (FTLS) vectorization [11] and the augmentation [13] for optimization of global error. These fast algorithms are used for extraction of approximation lines in 2D and 3D and for planes in 3D (see Figure 3).…”

Section: Implementation and Architecturementioning

confidence: 99%

“…These algorithms are also what make RTL truly unique among other similar projects. RTL provides an implementation of the fast total least squares (FTLS) vectorization [11] of the ordered point clouds -an optimized algorithm for approximation of ordered data, which provides computational performance similar to the point-eliminating methods [12], while preserving all the benefits of the TLS regression. An augmentation of the previous approach [13] for optimization of global error is present in RTL as well.…”

Section: (1) Overview Introductionmentioning

confidence: 99%

Robotic Template Library

Jelinek

Ligocki

Žalud

2021

JORS

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Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud processing, especially in robotic applications. The software package covers basic objects such as vectors, line segments, quaternions, rigid transformations, etc., however, its main contribution lies in the more advanced modules: The segmentation module for batch or stream clustering of point clouds, the fast vectorization module for approximation of continuous point clouds by geometric objects of higher grade and the LaTeX export module enabling automated generation of high-quality visual outputs. It is a header-only library written in C++17, uses the Eigen library as a linear algebra back-end, and is designed with high computational performance in mind. RTL can be used in all robotic tasks such as motion planning, map building, object recognition and many others, but the point cloud processing utilities are general enough to be employed in any field touching object reconstruction and computer vision applications as well.

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“…The second thing we want to explore is what effect will have different environment parametrization on these conditions. Because as we can see for example in [6,7] the environment structure does not have to always be represented by a point set and by exploiting assumption that the environment can be represented by some lower dimensional parametrization (for example that is composed strictly of planar elements [9]) we can reduce problem dimensionality for the price of adding additional nonlinearity to the edges which are connecting the environment and pose nodes. This can have actually two results either the additional nonlinearity makes the marginalization more difficult or the lower dimensionality will cause central limit theorem to be basically valid sooner and on the contrary makes the marginalization easier.…”

Section: Introductionmentioning

confidence: 99%

Effects of Environment Model Parametrization on Photogrametry Reconstruction

Klečka¹

2018

mendel

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This paper is aimed at a description of effects which have assumptions of specific environment structure on quality of recurrently conducted photogrammetry reconstruction. The theoretical part covers the description of three different assumptions of environment structure and mathematical derivation of two suitable recurrent estimators: one based on Extended Kalman filter and the second one based on Maximum likelihood method. The experimental part is introducing simple virtual environment which is observed by linear camera model and then reconstructed using predefined algorithms and assumptions.

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Fast total least squares vectorization

Cited by 9 publications

References 38 publications

On registration of vector maps with known correspondences

On registration of vector maps with known correspondences

Robotic Template Library

Effects of Environment Model Parametrization on Photogrametry Reconstruction

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