Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology Human eye sclera detection and tracking using a modified.

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Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology Human eye sclera detection and tracking using a modified time-adaptive self-organizing map Presenter : Shu-Ya Li Authors : Mohammad Hossein Khosravi, Reza Safabakhsh PR,

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Outline 2 Motivation Objective Methodology Experiments and Results Conclusion Personal Comments

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Motivation Automatic detection of human face and its components and tracking the component movements is an active research area in machine vision.  intelligent man–machine interfaces  driver behavior analysis  human identification/identity verification The original TASOM algorithm is found to have some weaknesses in this application. 3

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objectives Human eye sclera detection Human eye sclera tracking This paper proposed a new method for human eye sclera detection and tracking based on a modified TASOM. 4

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology overall 1. Eye detection 2. Eye feature extraction Iris center localization Eye corner detection Eye inner boundary detection using a modified TASOM 3. Human eye sclera tracking

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology - The TASOM-ACM algorithm (1) Weight initialization (2) Weight modification  weights w j are trained by the TASOM algorithm using the feature points x ∈ {x 1, x 2,..., x k }. (3) Contour updating (4) Weight updating (5) Neuron addition to or deletion from the TASOM network (6) Going to step (2) until some stopping criterion is satisfied. 66

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology - Modified TASOM The winning neuron identification Unused neuron removal 7

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology - Human eye sclera tracking 8 Edge change ratio (ECR) Neuron change ratio (NCR)

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 9

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Conclusion This paper proposed a new method for human eye sclera detection and tracking based on a modified TASOM. 10

Intelligent Database Systems Lab N.Y.U.S.T. I. M. Personal Comments Advantage  … Drawback  … Application  Image Recognition 11