mlsanityData to 14 Oct 2026

Periocular Biometrics and its Relevance to Partially Masked Faces: A Survey

arXiv 2203.15203 ↗First posted 29 Mar 2022cs.CVcited by 10

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Abstract (arXiv)

The performance of face recognition systems can be negatively impacted in the presence of masks and other types of facial coverings that have become prevalent due to the COVID-19 pandemic. In such cases, the periocular region of the human face becomes an important biometric cue. In this article, we present a detailed review of periocular biometrics. We first examine the various face and periocular techniques specially designed to recognize humans wearing a face mask. Then, we review different aspects of periocular biometrics: (a) the anatomical cues present in the periocular region useful for recognition, (b) the various feature extraction and matching techniques developed, (c) recognition across different spectra, (d) fusion with other biometric modalities (face or iris), (e) recognition on mobile devices, (f) its usefulness in other applications, (g) periocular datasets, and (h) competitions organized for evaluating the efficacy of this biometric modality. Finally, we discuss various challenges and future directions in the field of periocular biometrics.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 26 of its 202 references that are in the map. First posted on arXiv 29 Mar 2022.

Builds on

26 of 202 references.

References · 26

  1. 2020Masked Face Recognition Dataset and Applicationcited by 66
  2. 2019Occlusion Robust Face Recognition Based on Mask Learning with PairwiseDifferential Siamese Networkcited by 51
  3. 2020Masked Face Recognition for Secure Authenticationcited by 48
  4. 2021Masked Face Recognition Challenge: The InsightFace Track Reportcited by 41
  5. 2021Self-restrained Triplet Loss for Accurate Masked Face Recognitioncited by 32
  6. 2020The Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Studycited by 26
  7. 2020Face Mask Detection using Transfer Learning of InceptionV3cited by 23
  8. 2021MFR 2021: Masked Face Recognition Competitioncited by 23
  9. 2018A Survey on Periocular Biometrics Researchcited by 20
  10. 2016Grid Loss: Detecting Occluded Facescited by 17
  11. 2021Efficient Masked Face Recognition Method during the COVID-19 Pandemiccited by 16
  12. 2018Periocular Recognition Using CNN Features Off-the-Shelfcited by 13
14 more
  1. 2019Some Research Problems in Biometrics: The Future Beckonscited by 13
  2. 2021Boosting Masked Face Recognition with Multi-Task ArcFacecited by 13
  3. 2021Masked Face Recognition Challenge: The WebFace260M Track Reportcited by 12
  4. 2019Ocular Recognition Databases and Competitions: A Surveycited by 10
  5. 2019Cross-Sensor Periocular Biometrics in a Global Pandemic: Comparative Benchmark and Novel Multialgorithmic Approachcited by 9
  6. 2021Masked Face Recognition: Human vs. Machinecited by 9
  7. 2020Probing Fairness of Mobile Ocular Biometrics Methods Across Gender on VISOB 2.0 Datasetcited by 6
  8. 2019Deep Representations for Cross-spectral Ocular Biometricscited by 5
  9. 2020Cross-Spectral Periocular Recognition with Conditional Adversarial Networkscited by 4
  10. 2018Expression Recognition Using the Periocular Region: A Feasibility Studycited by 3
  11. 2013Robust Periocular Recognition By Fusing Sparse Representations of Color and Geometry Informationcited by 2
  12. 2020Smartphone Camera De-identification while Preserving Biometric Utilitycited by 2
  13. 2018Heterogeneity Aware Deep Embedding for Mobile Periocular Recognitioncited by 1
  14. 2018Cross-spectral Periocular Recognition: A Surveycited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 3; 2023: 1; 2024: 1; 2025: 3; 2026: 2.

10 papers.

  1. 2022Periocular Biometrics: A Modality for Unconstrained Scenarioscited by 10
  2. 2023One-Shot Learning for Periocular Recognition: Exploring the Effect of Domain Adaptation and Data Bias on Deep Representationscited by 4
  3. 2024Combined CNN and ViT features off-the-shelf: Another astounding baseline for recognitioncited by 4
  4. 2022A Survey on Computer Vision based Human Analysis in the COVID-19 Eracited by 3
  5. 2022Finger-NestNet: Interpretable Fingerphoto Verification on Smartphone using Deep Nested Residual Networkcited by 3
  6. 2025Exploring Complementarity and Explainability in CNNs for Periocular Verification Across Acquisition Distancescited by 0
  7. 2025Leveraging Large-Scale Face Datasets for Deep Periocular Recognition via Ocular Croppingcited by 0
  8. 2025Real-Time Drivers' Drowsiness Detection and Analysis through Deep Learningcited by 0
  9. 2026Periocular Soft Biometrics: A Survey and Applications to Multimedia Forensics and Disinformation Detectioncited by 0
  10. 2026Benchmarking CLIP for Zero-Shot Face and Periocular Gender Estimationcited by 0