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0136711cf4
Adds fitEllipseDirect to imgproc: The Direct least square (Direct) method by Fitzgibbon1999. New Tests are included for the methods. fitEllipseAMS Tests fitEllipseDirect Tests Comparative examples are added to fitEllipse.cpp in Samples.
967 lines
32 KiB
BibTeX
967 lines
32 KiB
BibTeX
@comment{Bib-it,
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This file was created by Bib-it 1.4
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97 entries written
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@ARTICLE{fitzgibbon1999,
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abstract = {This work presents a new efficient method for fitting
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ellipses to scattered data. Previous algorithms either
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fitted general conics or were computationally expensive. By
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minimizing the algebraic distance subject to the constraint
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4ac-b<sup>2</sup>=1, the new method incorporates the
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ellipticity constraint into the normalization factor. The
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proposed method combines several advantages: It is
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ellipse-specific, so that even bad data will always return
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an ellipse. It can be solved naturally by a generalized
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eigensystem. It is extremely robust, efficient, and easy to
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implement},
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author = {Fitzgibbon, Andrew and Pilu, Maurizio and Fisher, Robert B.},
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doi= {10.1109/34.765658},
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isbn= {0162-8828},
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issn= {01628828},
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journal = {IEEE Transactions on Pattern Analysis and Machine
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Intelligence},
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representation and estimation of complex planar curves in
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2-D surfaces in 3-D, and nonplanar space curves in 3-D.
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Curves and surfaces can be defined either parametrically or
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implicitly, with the latter representation used here. A
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planar curve is the set of zeros of a smooth function of
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two variables <e1>x</e1>-<e1>y</e1>, a surface is the set
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of zeros of a smooth function of three variables
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<e1>x</e1>-<e1>y</e1>-<e1>z</e1>, and a space curve is the
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intersection of two surfaces, which are the set of zeros of
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two linearly independent smooth functions of three
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surface of a complex object in 3-D can be represented as a
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subset of a single implicit surface, with similar results
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representation can be used for object recognition, object
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position estimation, and segmentation of objects into
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meaningful subobjects, that is, the detection of `interest
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regions' that are more complex than high curvature regions
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author = {Taubin, Gabriel},
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author={Forss{\'e}n, Per-Erik},
|
||
booktitle={Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on},
|
||
pages={1--8},
|
||
year={2007},
|
||
organization={IEEE}
|
||
}
|
||
@incollection{bottou2010large,
|
||
title={Large-scale machine learning with stochastic gradient descent},
|
||
author={Bottou, L{\'e}on},
|
||
booktitle={Proceedings of COMPSTAT'2010},
|
||
pages={177--186},
|
||
year={2010},
|
||
publisher={Springer}
|
||
}
|
||
@INPROCEEDINGS{Ke17,
|
||
author = {Ke, Tong and Roumeliotis, Stergios},
|
||
title = {An Efficient Algebraic Solution to the Perspective-Three-Point Problem},
|
||
booktitle = {Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on},
|
||
year = {2017},
|
||
organization = {IEEE}
|
||
}
|