Periocular Region

About: Periocular Region is a research topic. Over the lifetime, 256 publications have been published within this topic receiving 4424 citations.

Updates on upper eyelid blepharoplasty.

Abstract: The human face is composed of small functional and cosmetic units, of which the eyes and periocular region constitute the main point of focus in routine face-to-face interactions. This dynamic region plays a pivotal role in the expression of mood, emotion, and character, thus making it the most relevant component of the facial esthetic and functional unit. Any change in the periocular unit leads to facial imbalance and functional disharmony, leading both the young and the elderly to seek consultation, thus making blepharoplasty the surgical procedure of choice for both cosmetic and functional amelioration. The applied anatomy, indications of upper eyelid blepharoplasty, preoperative workup, surgical procedure, postoperative care, and complications would be discussed in detail in this review article.

Probabilistic Deformation Models for Challenging Periocular Image Verification

Abstract: The periocular region as a biometric trait has recently gained considerable traction, especially under challenging scenarios where reliable iris information is not available for human authentication. In this paper, we consider the problem of one-to-one (1 : 1) matching of highly nonideal periocular images captured in-the-wild under unconstrained imaging conditions. Such images exhibit considerable appearance variations, including nonuniform illumination variations, motion and defocus blur, off-axis gaze, and nonstationary pattern deformations. To address these challenges, we propose periocular probabilistic deformation models (PPDMs) that: 1) reduce the image matching problem to matching local image regions and 2) approximate the periocular distortions by local patch level spatial translations whose relationships are modeled by a Gaussian Markov random field. Given a periocular image pair, we determine the distortion-tolerant similarity metric by regularizing local match scores by the maximum a posteriori probability estimate of the relative local deformations between them. Unlike the existing global periocular image matching techniques, by accounting for local image deformations in the periocular matching process, PPDM exhibits greater tolerance to pattern variations. We demonstrate the effectiveness of our model via extensive evaluation on a large number of in-the-wild periocular images. We find that PPDMs outperform many benchmark 1 : 1 image matching techniques (improving verification rates at 0.1% false accept rate by ${\sim }30$ % over previous work and ${\sim }40$ % when compared with the best baseline) in challenging scenarios leading to state-of-the-art verification performance on multiple real-world periocular data sets.

Iris or Periocular? Exploring Sex Prediction from Near Infrared Ocular Images

Abstract: Recent research has explored the possibility of automatically deducing the sex of an individual based on near infrared (NIR) images of the iris. Previous articles on this topic have extracted and used only the iris region, while most operational iris biometric systems typically acquire the extended ocular region for processing. Therefore, in this work, we investigate the sex-predictive accuracy associated with four different regions: (a) the extended ocular region; (b) the iris-excluded ocular region; (c) the iris-only region and (d) the normalized iris-only region. We employ the BSIF (Binarized Statistical Image Feature) texture operator to extract features from these regions, and train a Support Vector Machine (SVM) to classify the extracted feature set as Male or Female. Experiments on a dataset containing 3314 images suggest that the iris region only provides modest sex-specific cues compared to the surrounding periocular region. This research further underscores the importance of using the periocular region in iris recognition systems.