Logo des Repositoriums
 

LVT Face Database: A benchmark database for visible and hidden face biometrics

dc.contributor.authorNélida Mirabet-Herranz, Jean-Luc Dugelay
dc.contributor.editorDamer, Naser
dc.contributor.editorGomez-Barrero, Marta
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorSequeira, Ana F.
dc.contributor.editorTodisco, Massimiliano
dc.contributor.editorUhl, Andreas
dc.date.accessioned2023-12-12T10:46:47Z
dc.date.available2023-12-12T10:46:47Z
dc.date.issued2023
dc.description.abstractAlthough the estimation of eHealth parameters from face visuals (images and videos) has grown as a major area of research in the past years, deep-learning-based models are still challenged by RGB lack of robustness, for instance with changing illumination conditions. As a means to overcome these limitations and to unlock new opportunities, thermal imagery has arisen as a favorable alternative to solidify different technologies such as heart rate estimation from faces. However, the reduced number of databases containing thermal imagery and the lack of health annotation of the subjects in them limits the exploration of this spectrum. Motivated by this, in this paper, we present our Label-EURECOM Visible and Thermal (LVT) Face Database for face biometrics. This database is the first that contains paired visible and thermal images and videos from 52 subjects with metadata of 22 soft biometrics and health parameters. Moreover, we establish the first study introducing the potential of thermal images for weight estimation from faces on our database.en
dc.identifier.isbn978-3-88579-733-3
dc.identifier.issn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43276
dc.language.isoen
dc.pubPlaceBonn
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2023
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-339
dc.subjectDatasets
dc.subjectEvaluation
dc.subjectBenchmarking
dc.subjectBiometrics in Healthcare
dc.subjectBanking
dc.subjectIoT
dc.titleLVT Face Database: A benchmark database for visible and hidden face biometricsen
dc.typeText/Conference Paper
mci.conference.date20.-22. September 2023
mci.conference.locationDarmstadt
mci.conference.sessiontitleFurther Conference Contributions
mci.reference.pages275-284

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
LNI_034.pdf
Größe:
319.03 KB
Format:
Adobe Portable Document Format