mlsanityData to 7 Oct 2026

A Survey on Periocular Biometrics Research

arXiv 1810.03360 ↗First posted 8 Oct 2018cs.CVcited by 20

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Abstract (arXiv)

Periocular refers to the facial region in the vicinity of the eye, including eyelids, lashes and eyebrows. While face and irises have been extensively studied, the periocular region has emerged as a promising trait for unconstrained biometrics, following demands for increased robustness of face or iris systems. With a surprisingly high discrimination ability, this region can be easily obtained with existing setups for face and iris, and the requirement of user cooperation can be relaxed, thus facilitating the interaction with biometric systems. It is also available over a wide range of distances even when the iris texture cannot be reliably obtained (low resolution) or under partial face occlusion (close distances). Here, we review the state of the art in periocular biometrics research. A number of aspects are described, including: i) existing databases, ii) algorithms for periocular detection and/or segmentation, iii) features employed for recognition, iv) identification of the most discriminative regions of the periocular area, v) comparison with iris and face modalities, vi) soft-biometrics (gender/ethnicity classification), and vii) impact of gender transformation and plastic surgery on the recognition accuracy. This work is expected to provide an insight of the most relevant issues in periocular biometrics, giving a comprehensive coverage of the existing literature and current state of the art.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Oct 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 5; 2023: 3; 2024: 3; 2025: 1; 2026: 2.

20 papers.

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  1. 2022Deep Learning for Iris Recognition: A Surveycited by 25
  2. 2021Biometrics in the Era of COVID-19: Challenges and Opportunitiescited by 11
  3. 2021On the Effect of Selfie Beautification Filters on Face Detection and Recognitioncited by 10
  4. 2022Periocular Biometrics and its Relevance to Partially Masked Faces: A Surveycited by 9
  5. 2022Periocular Biometrics: A Modality for Unconstrained Scenarioscited by 9
  6. 2021Facial Masks and Soft-Biometrics: Leveraging Face Recognition CNNs for Age and Gender Prediction on Mobile Ocular Imagescited by 7
  7. 2021Attribute-Based Deep Periocular Recognition: Leveraging Soft Biometrics to Improve Periocular Recognitioncited by 5
  8. 2023One-Shot Learning for Periocular Recognition: Exploring the Effect of Domain Adaptation and Data Bias on Deep Representationscited by 4
  9. 2023An Explainable Model-Agnostic Algorithm for CNN-based Biometrics Verificationcited by 4
  10. 2021Selfie Periocular Verification using an Efficient Super-Resolution Approachcited by 3
  11. 2022A Survey on Computer Vision based Human Analysis in the COVID-19 Eracited by 3
  12. 2024Combined CNN and ViT features off-the-shelf: Another astounding baseline for recognitioncited by 3
8 more
  1. 2021AI perspectives in Smart Cities and Communities to enable road vehicle automation and smart traffic controlcited by 2
  2. 2022Compact multi-scale periocular recognition using SAFE featurescited by 2
  3. 2024VRBiom: A New Periocular Dataset for Biometric Applications of HMDcited by 1
  4. 2023Log-Likelihood Score Level Fusion for Improved Cross-Sensor Smartphone Periocular Recognitioncited by 0
  5. 2024Understanding and Improving CNNs with Complex Structure Tensor: A Biometrics Studycited by 0
  6. 2025Leveraging Large-Scale Face Datasets for Deep Periocular Recognition via Ocular Croppingcited by 0
  7. 2026Explicit Over Implicit: Enhancing CNNs Via Complex Structure Tensor Representations for Periocular Recognitioncited by 0
  8. 2026Periocular Soft Biometrics: A Survey and Applications to Multimedia Forensics and Disinformation Detectioncited by 0