Periocular Region

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

Reperfusion of Free Full-Thickness Skin Grafts in Periocular Reconstructive Surgery Monitored Using Laser Speckle Contrast Imaging

Abstract: PURPOSE: Free skin grafts are frequently used in reconstructive surgery. However, little is known about the course of reperfusion due to the previous lack of reliable perfusion monitoring techniques. The aim of this study was to use state-of-the-art laser speckle contrast imaging to monitor free skin grafts in the periocular area.METHODS: Seven patients needing surgery due to tumor removal or cicatricial ectropion in the periocular region underwent reconstructive surgery using free skin grafts from either the contralateral upper eyelid or the upper inner arm. The free skin grafts measured 10-30 mm horizontally and 9-30 mm vertically. Blood perfusion was monitored using laser speckle contrast imaging immediately postoperatively (0 weeks) and at follow-up after 1, 3, and 7 weeks.RESULTS: All grafts were reperfused gradually during healing, the median value being 46% in the central part of the graft after 1 week and 79% after 3 weeks. The grafts were completely reperfused after 7 weeks. No difference was observed in the rate of reperfusion between the center and periphery of the grafts (p = not significant). The cosmetic and functional outcome was excellent in all but 1 patient, who developed ectropion that had to be surgically corrected.CONCLUSIONS: Skin grafts in the periorbital area are fully reperfused after 7 weeks. The periocular area is known to be well-vascularized and thus forgiving to reconstructive surgery. Future investigations of the reperfusion of free skin grafts in other parts of the body or in higher-risk populations should be carried out.

Clinical Anatomy of the Periocular Region

Abstract: The aims of this article are twofold: (1) to provide the facial plastic surgeon with a comprehensive and up-to-date overview of periocular anatomy including the brow, midface, and temporal region and (2) to highlight important anatomical relationships that must be appreciated in order to achieve the best possible functional and aesthetic surgical outcomes.

Biometric Identification Using the Periocular Region

Abstract: The face is the fundamental basis for the identification/recognition of a person. Recognition of a individual by the face data and methods to extract the unique facial feature points from the facial image have been significantly increased during the last decade. The periocular region has become the powerful alternative for unconstrained biometrics with better robustness and high discrimination ability. In this paper, multiple descriptors are used for deriving the discriminative features of the periocular region and city block distance is used to compute the similarity between the feature vectors. Feature extraction techniques employed in recognition using the periocular region are Local Binary Patterns (LBP), Local Phase Quantization (LPQ) and Speeded Up Robust Feature (SURF). Results of Periocular modality are then compared with the results of face patterns. Periocular region showed significant accuracies compared to face with only using 25% of the full face. Experimentations are carried on FRGC database, and accuracies of both the periocular and face regions are compared.

Relevant features for gender classification in NIR periocular images

Abstract: Most gender classifications methods from near-infrared (NIR) images have used iris information. Recent work has explored the use of the whole periocular iris region which has surprisingly achieved better results. This suggests the most relevant information for gender classification is not located in the iris as expected. In this work, the authors analyse and demonstrate the location of the most relevant features that describe gender in periocular NIR images and evaluate their influence in classification. Experiments show that the periocular region contains more gender information than the iris region. They extracted several features (intensity, texture, and shape) and classified them according to their relevance using the XgBoost algorithm. Support vector machine and nine ensemble classifiers were used for testing gender accuracy when using the most relevant features. The best classification results were obtained when 4000 features located on the periocular region were used (89.22%). Additional experiments with the full periocular iris images versus the iris-occluded images were performed. The gender classification rates obtained were 84.35 and 85.75%, respectively. From results, they suggest focusing only on the surrounding area of the iris. This allows us to realise a faster classification of gender from NIR periocular images.

Extract Features from Periocular Region to Identify the Age Using Machine Learning Algorithms

Abstract: Latest studies done on huge data collected from aging features proved that the performance of facial image based age estimation is low and need to be improved. One of the significant biometric traits for human recognition or search is Human age. Age assessment is very much exigent over other pattern recognition problems since the aging differs from person to person. This paper proposes a new framework that uses periocular region for age feature extraction and application of hybrid algorithm for age recognition. Firstly, preprocessing and periocular region normalization is done to acquire age invariant features. Secondly, the periocular region that underwent preprocessing is analyzed using hybrid approach, a novel machine algorithm that combines both SVM and kNN. The proposed technique generates the best recognition outputs.