Face Recognition - PowerPoint PPT Presentation

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Face Recognition

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Isolate Largest Contour. Profile Curve. Curve Matching. Parse Data to Extract Costs ... Fill Region Up Until Contour. I. Pre-Processing Cont'd. Remove Hair-Line Noise ... – PowerPoint PPT presentation

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Title: Face Recognition


1
Face Recognition
  • Joshua I. Cohen

2
Overview
  • Cutting Edge
  • Constraints
  • - Speed
  • - Accuracy

3
Data Acquisition
  • Digital Camera

4
Data Acquisition Contd
5
Data Acquisition Contd
  • Video Camera w/ IR Filtering

6
Algorithm
  1. Pre-Processing
  2. Convert .bmp to .pgm
  3. Isolate Largest Contour
  4. Profile Curve
  5. Curve Matching
  6. Parse Data to Extract Costs

7
I. Pre-Processing
  • Starting Images

8
I. Pre-Processing Contd
  • Convert To Gray Scale

9
I. Pre-Processing Contd
  • Binary Threshold

10
I. Pre-Processing Contd
  • Centroid

11
I. Pre-Processing Contd
  • Filter Noise Using Connected Regions

12
I. Pre-Processing Contd
  • Fill Region Up Until Contour

13
I. Pre-Processing Contd
  • Remove Hair-Line Noise

14
I. Pre-Processing Contd
  • Crop Image Area

15
I. Pre-Processing Contd
  • Normalize
  • Fill Border To Black
  • Save to .bmp File

16
II. Convert .bmp to .pgm
  • SUN utility
  • convert-to-pgm f1.bmp f2.pgm

.bmp ? .pgm
17
III. Isolate Largest Contour
  • SGI utility
  • computeBoundaryLength f1.pgm smooth 1

CONTOUROPEN/CLOSEnx1 y1 x2 y2 xn yn
.con file
18
IV. Profile Curve
19
V. Curve Matching
  • OpenCurveMatch f1.con f2.con 10 1
  • Intrinsic Properties length and curvature
  • Optimal Correspondence
  • Alignment Curve
  • Invariant rotations, translations, viewpoint
    variation, articulation, occlusions

20
VI. Parse Data to Extract Costs
  • f1-points-f2-points-match.txt
  • cost-summary.txt

f1 f1 0 f1 f2 403.668 f1 f3 468.081 f1 f4
454.315 f2 f2 0
21
Preliminary Results
  • Amir vs Everyone

22
Preliminary Results Contd
  • Brian vs Ming / Vinesh

23
Preliminary Results Contd
  • Tom vs Vinesh

24
Preliminary Results Summary
  • 50-60 success rate
  • margin of error very small
  • - 450 or less is a match
  • - greater than 450 not a match

25
Remaining Issues
  • Angle

Eye
26
Remaining Issues Contd
  • Angle Contd

Normal
Forehead / Eye
27
Remaining Issues Contd
  • Hair-Line
  • Normalizing ? Distortion

28
Possible Solutions
  • Use More Criteria (local extrema)
  • - contour of nose
  • - contour of chin
  • Better Method to Filter Hair-Line
  • Curve Match Segments of Face Profile

29
References
  • Ross Cutler, Face Recognition Using Infrared
    Images and Eigenfaces, April 1996.
  • Thomas B. Sebastian, Philip N. Klein, Benjamin B.
    Kimia, Alignment-based Recognition of Shape
    Outlines, 2001.
  • Zdravko Liposcak and Sven Loncaric, A
    Scale-Space Approach to Face Recognition from
    Profiles, 1999.
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