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Visual localization by linear combination of image descriptors

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00187150" target="_blank" >RIV/68407700:21230/11:00187150 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Visual localization by linear combination of image descriptors

  • Original language description

    We seek to predict the GPS location of a query image given a database of images localized on a map with known GPS locations. The contributions of this work are three-fold: (1) we formulate the image-based localization problem as a regression on an imagegraph with images as nodes and edges connecting close-by images; (2) we design a novel image matching procedure, which computes similarity between the query and pairs of database images using edges of the graph and considering linear combinations of their feature vectors. This improves generalization to unseen viewpoints and illumination conditions, while reducing the database size; (3) we demonstrate that the query location can be predicted by interpolating locations of matched images in the graph without the costly estimation of multi-view geometry. We demonstrate benefits of the proposed image matching scheme on the standard Oxford building benchmark, and show localization results on a database of 8,999 panoramic Google Street View.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2011

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)

  • ISBN

    978-1-4673-0063-6

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    102-109

  • Publisher name

    IEEE Computer Society Press

  • Place of publication

    Los Alamitos

  • Event location

    Barcelona

  • Event date

    Nov 6, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article