On Recognizing Occluded Faces in the Wild

Mustafa Ekrem Erakın, Ugur Demir, Hazım Kemal Ekenel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Facial appearance variations due to occlusion has been one of the main challenges for face recognition systems. To facilitate further research in this area, it is necessary and important to have occluded face datasets collected from real-world, as synthetically generated occluded faces cannot represent the nature of the problem. In this paper, we present the Real World Occluded Faces (ROF) dataset, that contains faces with both upper face occlusion, due to sunglasses, and lower face occlusion, due to masks. We propose two evaluation protocols for this dataset. Benchmark experiments on the dataset have shown that no matter how powerful the deep face representation models are, their performance degrades significantly when they are tested on real-world occluded faces. It is observed that the performance drop is far less when the models are tested on synthetically generated occluded faces. The ROF dataset and the associated evaluation protocols are publicly available at the following link https://github.com/ekremerakin/RealWorldOccludedFaces.

Original languageEnglish (US)
Title of host publicationBIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group
EditorsArslan Bromme, Christoph Busch, Naser Damer, Antitza Dantcheva, Marta Gomez-Barrero, Kiran Raja, Christian Rathgeb, Ana F. Sequeira, Andreas Uhl
PublisherGesellschaft fur Informatik (GI)
Pages189-196
Number of pages8
ISBN (Electronic)9783885797098
StatePublished - 2021
Event20th International Conference of the Biometrics Special Interest Group, BIOSIG 2021 - Darmstadt, Germany
Duration: Sep 15 2021Sep 17 2021

Publication series

NameLecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
VolumeP-315
ISSN (Print)1617-5468

Conference

Conference20th International Conference of the Biometrics Special Interest Group, BIOSIG 2021
Country/TerritoryGermany
CityDarmstadt
Period9/15/219/17/21

Keywords

  • Deep learning
  • Face occlusion
  • Face recognition
  • Real-world occluded faces

ASJC Scopus subject areas

  • Computer Science Applications

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