Pupil Localization Using Geodesic Distance View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-11-10

AUTHORS

Radovan Fusek

ABSTRACT

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. More... »

PAGES

433-444

References to SciGraph publications

  • 2015. ExCuSe: Robust Pupil Detection in Real-World Scenarios in COMPUTER ANALYSIS OF IMAGES AND PATTERNS
  • 2001-08-17. Robust Face Detection Using the Hausdorff Distance in AUDIO- AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION
  • Book

    TITLE

    Advances in Visual Computing

    ISBN

    978-3-030-03800-7
    978-3-030-03801-4

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-030-03801-4_38

    DOI

    http://dx.doi.org/10.1007/978-3-030-03801-4_38

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1109840786


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