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Pupil localization using geodesic distance

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241535" target="_blank" >RIV/61989100:27240/18:10241535 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-030-03801-4_38" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-03801-4_38</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-03801-4_38" target="_blank" >10.1007/978-3-030-03801-4_38</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Pupil localization using geodesic distance

  • Original language description

    The main contributions of the presented paper can be summarized as follows. Firstly, we introduce a unique and robust dataset of human eyes that can be used in many detection and recognition scenarios, especially for the recognition of driver drowsiness, gaze direction, or eye-blinking frequency. The dataset consists of approximately 85,000 different eye regions that were captured using various near-infrared cameras, various resolutions, and various lighting conditions. The images are annotated into many categories. Secondly, we present a new method for pupil localization that is based on the geodesic distance. The presented experiments show that the proposed method outperforms the state-of-the-art methods in this area. (C) Springer Nature Switzerland AG 2018.

  • 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

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 11241

  • ISBN

    978-3-030-03800-7

  • ISSN

    0302-9743

  • e-ISSN

    1611-3349

  • Number of pages

    12

  • Pages from-to

    433-444

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Las Vegas

  • Event date

    Nov 19, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article