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On Evaluating Pixel-Level Face Image Quality Assessment

Huber, Marco ; Terhörst, Philipp ; Kirchbuchner, Florian ; Damer, Naser ; Kuijper, Arjan (2022)
On Evaluating Pixel-Level Face Image Quality Assessment.
30th European Signal Processing Conference. Belgrade, Serbia (29.08.-02.09.2022)
doi: 10.23919/EUSIPCO55093.2022.9909844
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

A decisive factor for face recognition performance is face image quality (FIQ). It describes the utility of face images for automatic recognition. While this FIQ has conventionally been considered as a scalar for the whole image, emerging works suggest assessing pixel-level FIQs to provide higher explainability. However, the value of pixel-level qualities as a measure of utility (value for recognition) is not yet investigated. In this work, we address this by presenting two evaluation schemes, deletion evaluation curve (DEC) and insertion evaluation curve (IEC). The DEC investigates the change in recognition performance as pixels are deleted based on their quality. Complementary, the IEC reports the change in recognition performance as pixels are inserted based on their quality into a blurred image. Since pixel-level face image quality assessment (PLFIQA) methods assign high values to pixels that contain discriminant information, the recognition performance should decrease or increase when they are removed or added, respectively. We have successfully demonstrated the proposed evaluation scheme on two face recognition solutions by comparing a recently proposed PLFIQA method to a random baseline. With the growing interest in explainable face recognition, the proposed metrics will enable adequate comparison of future advances in pixel-level quality assessment.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2022
Autor(en): Huber, Marco ; Terhörst, Philipp ; Kirchbuchner, Florian ; Damer, Naser ; Kuijper, Arjan
Art des Eintrags: Bibliographie
Titel: On Evaluating Pixel-Level Face Image Quality Assessment
Sprache: Englisch
Publikationsjahr: 18 Oktober 2022
Verlag: EURASIP
Buchtitel: 30th European Signal Processing Conference (EUSIPCO 2022): Proceedings
Veranstaltungstitel: 30th European Signal Processing Conference
Veranstaltungsort: Belgrade, Serbia
Veranstaltungsdatum: 29.08.-02.09.2022
DOI: 10.23919/EUSIPCO55093.2022.9909844
URL / URN: https://ieeexplore.ieee.org/document/9909844
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Kurzbeschreibung (Abstract):

A decisive factor for face recognition performance is face image quality (FIQ). It describes the utility of face images for automatic recognition. While this FIQ has conventionally been considered as a scalar for the whole image, emerging works suggest assessing pixel-level FIQs to provide higher explainability. However, the value of pixel-level qualities as a measure of utility (value for recognition) is not yet investigated. In this work, we address this by presenting two evaluation schemes, deletion evaluation curve (DEC) and insertion evaluation curve (IEC). The DEC investigates the change in recognition performance as pixels are deleted based on their quality. Complementary, the IEC reports the change in recognition performance as pixels are inserted based on their quality into a blurred image. Since pixel-level face image quality assessment (PLFIQA) methods assign high values to pixels that contain discriminant information, the recognition performance should decrease or increase when they are removed or added, respectively. We have successfully demonstrated the proposed evaluation scheme on two face recognition solutions by comparing a recently proposed PLFIQA method to a random baseline. With the growing interest in explainable face recognition, the proposed metrics will enable adequate comparison of future advances in pixel-level quality assessment.

Freie Schlagworte: Biometrics, Face recognition, Deep learning, Machine learning
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing
Hinterlegungsdatum: 24 Nov 2022 08:29
Letzte Änderung: 27 Feb 2023 11:12
PPN: 50518317X
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