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Panorama to panorama matching for location recognition

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00312202" target="_blank" >RIV/68407700:21230/17:00312202 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1145/3078971.3079033" target="_blank" >http://dx.doi.org/10.1145/3078971.3079033</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3078971.3079033" target="_blank" >10.1145/3078971.3079033</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Panorama to panorama matching for location recognition

  • Original language description

    Location recognition is commonly treated as visual instance retrieval on “street view” imagery. i.e. dataset items and queries are panoramic views, i.e. groups of images taken at a single location. This work introduces a novel panorama-to-panorama matching process, either by aggregating features of individual images in a group or by explicitly constructing a larger panorama. In either case, multiple views are used as queries. We reach near perfect location recognition on a standard benchmark with only four query views.

  • 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

    <a href="/en/project/LL1303" target="_blank" >LL1303: Large Scale Category Retrieval</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

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

    ICMR '17 Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval

  • ISBN

    978-1-4503-4701-3

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    392-396

  • Publisher name

    ACM

  • Place of publication

    New York

  • Event location

    Bucharest

  • Event date

    Jun 6, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article