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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.

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Presentation on theme: "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."— Presentation transcript:

1 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, 2008 1

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

3 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

4 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

5 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

6 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

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

8 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)

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

10 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

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


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