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Tour Presentation
Tour Presentation
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Tour Presentation
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Tour Presentation
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Tour Presentation

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  • 1. Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    1
  • 2. Biometrics and Pattern Recognition Lab
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    2
    Human Centered Computing Division
    Clemson University, Spring 2010
  • 3. About Us
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    3
  • 4. Biometrics and Pattern Recognition Lab
    Established in Summer 2006
    Formerly the Image and Video Analysis Lab (IVAL)‏
    In 2008, became part of the Center of Advanced Studies in Identity Sciences (CASIS) with CMU, UNCW, and NC A&T University.
    4
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
  • 5. Biometrics?
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    5
  • 6. (Bio)(Metrics)‏
    Bio
    Life
    Metrics
    To measure
    Biometrics:
    The science of identifying or authenticating an individual’s identity based on behavioural or physiological characteristics.
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    6
  • 7. Biometric Characteristics
    Physical Characteristics
    Iris
    Retina
    Vein Pattern
    Hand Geometry
    Face
    Fingerprint
    Behavioural Characteristics
    Keystroke dynamics
    Signature dynamics
    Voice
    Gait
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    7
  • 8. Why Biometrics?
    Eliminate memorization
    Users don’t have to memorize features of their voice, face, eyes, or fingerprints
    Eliminate misplaced tokens
    Users won’t forget to bring fingerprints to work
    Can’t be delegated
    Users can’t lend fingers or faces to someone else
    Often unique
    Save money and maintain database integrity by eliminating duplicate enrollments
    8
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
  • 9. Biometric System
    Verification (1:1)
    Identification (1:N)
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    9
  • 10. Purpose
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    10
  • 11. Two main research goals
    To produce:
    Usable Biometrics
    • It might have 100% performance, but if it isn’t feasible in the real world, who cares?
    Unconstrained Biometrics
    • At present, good recognition rates depend on a lot of variables being just right, or at least consistent
    • 12. We would like to reduce the dependency or get rid of it altogether
    11
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
  • 13. Constraints
    Some common constraints are lighting, non-uniform distance, pose, expression, time lapse, occlusion
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    12
    Typical image used in facial recognition
    Unconstrained image
  • 14. Periocular Region Recognition
    Feature Reduction using Computational Intelligence
    Aging Effects on Facial Recognition
    Effects of Demographics on Facial Recognition
    Soft Biometrics
    Projects
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    13
  • 15. Periocular Region Recognition
    Relaxes image quality (location of iris, focus, blurring) on iris images
    Could be used if more of the face is occluded
    Currently looking at texture, color, and eye shape
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    14
  • 16. Feature Reduction using Computational Intelligence
    General Regression Neural Network (GRNN)
    Reduce the size of the features to enable faster, more portable biometric applications
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    15
  • 17. Aging Effects on Facial Recognition
    Looking at an image of a person, can we reliably predict
    what age they are?
    what they will look like in so many years?
    or what they looked like in the past?
    Relaxes time lapse constraint
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    16
  • 18. Demographics
    How do demographics affect recognition?
    Older easier to recognize than younger
    Males easier than females
    Why do some algorithms work better on certain populations than others?
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    17
  • 19. Soft Biometrics
    What if we don’t have enough information to identify the person?
    We would like to know as much about them as possible: age, gender, ...
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    18
  • 20. Questions?
    Clemson University
    School of Computing
    Biometrics and Pattern Recognition Lab Director: Damon Woodard, PhD
    19

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