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Selecting Image Pairs for SfM by Introducing Jaccard Similarity

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F17%3A00329401" target="_blank" >RIV/68407700:21730/17:00329401 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/7986764" target="_blank" >https://ieeexplore.ieee.org/document/7986764</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.23919/MVA.2017.7986764" target="_blank" >10.23919/MVA.2017.7986764</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Selecting Image Pairs for SfM by Introducing Jaccard Similarity

  • Original language description

    We present a new approach for selecting image pairs that are more likely to match in Structure from Motion (SfM). We propose to use Jaccard Similarity (JacS) which shows how many different visual words is shared by an image pair. In our method, the similarity between images is evaluated using JacS of bag-of-visual-words in addition to tf-idf, which is popular for this purpose. To evaluate the efficiency of our method, we carry out experiments on our original datasets as well as on Pantheon dataset, which is derived from Flickr. The result of our method using both JacS and tf-idf is better than the results of a standard method using tf-idf only.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • 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

  • Continuities

    R - Projekt Ramcoveho programu EK

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Machine Vision Applications (MVA), 2017 15th IAPR International Conference on

  • ISBN

    978-4-901122-16-0

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    25-29

  • Publisher name

    IEEE

  • Place of publication

    Piscataway

  • Event location

    Nagoya

  • Event date

    May 8, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000426950300007