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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. Outline. Motivation Objective Methodology Experiments and Results Conclusion - PowerPoint PPT Presentation
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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, 2008 1
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.
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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 wj are trained by the TASOM algorithm using the feature points x {x∈ 1, x2, . . . , xk}.
(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.
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Intelligent Database Systems Lab
N.Y.U.S.T.I. M.Methodology - Modified TASOM
The winning neuron identification
Unused neuron removal
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Intelligent Database Systems Lab
N.Y.U.S.T.I. M.Methodology - Human eye sclera tracking
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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
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