MODS: Fast and robust method for two-view matching

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00235507" target="_blank" >RIV/68407700:21230/15:00235507 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1016/j.cviu.2015.08.005" target="_blank" >http://dx.doi.org/10.1016/j.cviu.2015.08.005</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cviu.2015.08.005" target="_blank" >10.1016/j.cviu.2015.08.005</a>

Result language

angličtina

Original language name

MODS: Fast and robust method for two-view matching

Original language description

Abstract A novel algorithm for wide-baseline matching called MODS - matching on demand with view synthesis - is presented. The MODS algorithm is experimentally shown to solve a broader range of wide-baseline problems than the state of the art while beingnearly as fast as standard matchers on simple problems. The apparent robustness vs. speed trade-off is finessed by the use of progressively more time-consuming feature detectors and by on-demand generation of synthesized images that is performed until areliable estimate of geometry is obtained. We introduce an improved method for tentative correspondence selection, applicable both with and without view synthesis. A modification of the standard first to second nearest distance rule increases the numberof correct matches by 5-20% at no additional computational cost. Performance of the MODS algorithm is evaluated on several standard publicly available datasets, and on a new set of geometrically challenging wide baseline problems that is

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

—

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)

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computer Vision and Image Understanding

ISSN

1077-3142

e-ISSN

—

Volume of the periodical

141

Issue of the periodical within the volume

december

Country of publishing house

US - UNITED STATES

Number of pages

13

Pages from-to

81-93

UT code for WoS article

000364981500007

EID of the result in the Scopus database

2-s2.0-84948571032