Efficient energy-based topological outlier rejection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00324016" target="_blank" >RIV/68407700:21230/18:00324016 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1077314218301152?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1077314218301152?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.cviu.2018.07.002" target="_blank" >10.1016/j.cviu.2018.07.002</a>
Alternative languages
Result language
angličtina
Original language name
Efficient energy-based topological outlier rejection
Original language description
An approach is proposed for outlier rejection from a set of 2D point correspondences which does not require any underlying models, e.g. fundamental matrix. The solution is obtained by minimizing an energy originated from the neighborhood-graphs in both images using a grab-cut-like algorithm: iterated graph-cut and re-fitting. The method is validated on publicly available datasets, it is real time for most of the problems and achieves more accurate results than RANSAC and its state-of-the-art variants in terms of outlier rejection ratio. It is applicable to scenes where a single fundamental matrix is not estimable, e.g. non-rigid or degenerate ones.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
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
Computer Vision and Image Understanding
ISSN
1077-3142
e-ISSN
1090-235X
Volume of the periodical
174
Issue of the periodical within the volume
September
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
70-81
UT code for WoS article
000454184700007
EID of the result in the Scopus database
2-s2.0-85051502921