Efficient Recovery of Essential Matrix From Two Affine Correspondences
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00324018" target="_blank" >RIV/68407700:21230/18:00324018 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8392782" target="_blank" >https://ieeexplore.ieee.org/document/8392782</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TIP.2018.2849866" target="_blank" >10.1109/TIP.2018.2849866</a>
Alternative languages
Result language
angličtina
Original language name
Efficient Recovery of Essential Matrix From Two Affine Correspondences
Original language description
We propose a method to estimate the essential matrix using two affine correspondences for a pair of calibrated perspective cameras. Two novel, linear constraints are derived between the essential matrix and a local affine transformation. The proposed method is also applicable to the over-determined case. We extend the normalization technique of Hartley to local affinities and show how the intrinsic camera matrices modify them. Even though perspective cameras are assumed, the constraints can straightforwardly be generalized to arbitrary camera models since they describe the relationship between local affinities and epipolar lines (or curves). Benefiting from the low number of exploited points, it can be used in robust estimators, e.g. RANSAC, as an engine, thus leading to significantly less iterations than the traditional point-based methods. The algorithm is validated both on synthetic and publicly available data sets and compared with the state-of-the-art. Its applicability is demonstrated on two-view multi-motion fitting, i.e., finding multiple fundamental matrices simultaneously, and outlier rejection.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
O - Projekt operacniho programu
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Image Processing
ISSN
1057-7149
e-ISSN
1941-0042
Volume of the periodical
27
Issue of the periodical within the volume
11
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
5328-5337
UT code for WoS article
000440203500010
EID of the result in the Scopus database
2-s2.0-85049090983