Pupil Lovalization And Tracking For Video-Based Iris Biometrics
In this paper, we are interested in iris biometric applications. More precisely, our contribution consists in designing both a pupil detection and a tracking procedure from video sequences acquired by low-cost webcams. The novelty of our approach relies on the fact that it is operational even with a minimal user cooperation and, under bad illuminations and acquisition conditions. A robust classification algorithm is designed to detect the pupil. Moreover, a pupil tracker based on the extended Kalman filter is applied in order to reduce the processing time. Experimental results are performed in order to evaluate the performances of the proposed detection and tracking system
Code (0)
등록된 구현이 없습니다.
Tasks
Pupil DetectionRobust classificationSimilar Papers 제목 키워드 기반
EllSeg: An Ellipse Segmentation Framework for Robust Gaze Tracking
Ellipse fitting, an essential component in pupil or iris tracking based video oculography, is performed on previously segmented eye parts generated using various computer vision techniques. Several factors, such as occlu…
PositionSegmentationLearning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samples
Subject matching performance in iris biometrics is contingent upon fast, high-quality iris segmentation. In many cases, iris biometrics acquisition equipment takes a number of images in sequence and combines the segmenta…
Iris SegmentationSegmentationCondSeg: Ellipse Estimation of Pupil and Iris via Conditioned Segmentation
Parsing of eye components (i.e. pupil, iris and sclera) is fundamental for eye tracking and gaze estimation for AR/VR products. Mainstream approaches tackle this problem as a multi-class segmentation task, providing only…
Gaze EstimationSegmentationArtificial Pupil Dilation for Data Augmentation in Iris Semantic Segmentation
Biometrics is the science of identifying an individual based on their intrinsic anatomical or behavioural characteristics, such as fingerprints, face, iris, gait, and voice. Iris recognition is one of the most successful…
Data AugmentationIris RecognitionIris SegmentationPupil Dilation+2Center of circle after perspective transformation
Video-based glint-free eye tracking commonly estimates gaze direction based on the pupil center. The boundary of the pupil is fitted with an ellipse and the euclidean center of the ellipse in the image is taken as the ce…