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Exploring 3D Face Reconstruction and Fusion Methods for Face Verification: A Case-Study in Video Surveillance

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F25%3A00143561" target="_blank" >RIV/00216224:14310/25:00143561 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-031-91575-8_16" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-91575-8_16</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-91575-8_16" target="_blank" >10.1007/978-3-031-91575-8_16</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring 3D Face Reconstruction and Fusion Methods for Face Verification: A Case-Study in Video Surveillance

  • Original language description

    3D face reconstruction (3DFR) algorithms are based on specific assumptions tailored to distinct application scenarios. These assumptions limit their use when acquisition conditions, such as the subject's distance from the camera or the camera's characteristics, are different than expected, as typically happens in video surveillance. Additionally, 3DFR algorithms follow various strategies to address the reconstruction of a 3D shape from 2D data, such as statistical model fitting, photometric stereo, or deep learning. In the present study, we explore the application of three 3DFR algorithms representative of the SOTA, employing each one as the template set generator for a face verification system. The scores provided by each system are combined by score-level fusion. We show that the complementarity induced by different 3DFR algorithms improves performance when tests are conducted at never-seen-before distances from the camera and camera characteristics (cross-distance and cross-camera settings), thus encouraging further investigations on multiple 3DFR-based approaches.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    COMPUTER VISION-ECCV 2024 WORKSHOPS, PT XIII

  • ISBN

    9783031915741

  • ISSN

    0302-9743

  • e-ISSN

    1611-3349

  • Number of pages

    17

  • Pages from-to

    257-273

  • Publisher name

    SPRINGER INTERNATIONAL PUBLISHING AG

  • Place of publication

    Cham

  • Event location

    Milan, ITALY

  • Event date

    Sep 29, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001544986600016