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Face Detection Face Detection and Gender Recognition and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

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RGB Colour-Space Histograms

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Page 1: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Face Detection Face Detection and Gender Recognitionand Gender Recognition

EE368 Project Report

Michael BaxChunlei Liu

Ping Li

28 May 2003

Page 2: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Colour SpacesColour Spaces

Page 3: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

RGB Colour-Space HistogramsRGB Colour-Space Histograms

Page 4: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

HSV Colour-Space HistogramsHSV Colour-Space Histograms

Page 5: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Empirical PDF ApproximationEmpirical PDF Approximation

Page 6: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Pixel Classification Error (RGB)Pixel Classification Error (RGB)

Page 7: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Pixel Classification Error (HSV)Pixel Classification Error (HSV)

Page 8: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Input ImageInput Image

Page 9: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Pixel Segmentation Pixel Segmentation Using the RGB Pixel PDFUsing the RGB Pixel PDF

Page 10: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Non-Face Object RemovalNon-Face Object Removal

Page 11: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Size-based Size-based Non-Face Object RemovalNon-Face Object Removal

Page 12: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Location-based Location-based Non-Face Object RemovalNon-Face Object Removal

Page 13: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Object Size Threshold CorrectionObject Size Threshold Correction

Page 14: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

PCA-basedPCA-basedNon-Face Object RemovalNon-Face Object Removal

Page 15: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Connected Component Connected Component AnalysisAnalysis

Low pass filtering, hole filling and background rejection

Identification of connected faces based on statistical analysis

Iterative separation of connected regions

Preprocessing

Connected faces identification

Face separation

Page 16: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Connected ComponentsConnected Components

Page 17: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Component SeparationComponent Separation

Page 18: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Separated ComponentsSeparated Components

Page 19: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Component IdentificationComponent Identification

Template matching and peak thresholding to remove remaining non-face objects

Removal of repeated faces segments using a distance constraint

Page 20: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Face Position RefinementFace Position Refinement

The face centre is located at the bridge of the nose

The centroid of the segmented face is somewhat inaccurate in finding face centres

Multi-scale, high threshold template matching finds centres more accurately

Use centroid for remaining faces

Page 21: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Image Pyramid-based Image Pyramid-based Template MatchingTemplate Matching

Training face preprocessing– Training faces were rotation compensated,

registered, and resampled in greyscale– Resampled faces were averaged and masked

Greyscale input image pyramid composition– 20% scale increments

Normalized cross-correlation with nose bridge-centred average face template

Page 22: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Finding Faces Finding Faces with Template Matchingwith Template Matching

High threshold for accurate centre location

Moderate threshold for robust backup face location – if morphological

subsystem gives unexpected results

Page 23: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Gender DetectionGender Detection

Mean intensity Template matching

using average of each female face

Biased towards missing female faces to avoid false-positive penalty (9:1)

Page 24: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Face Detection ResultsFace Detection Results

Page 25: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

Image Hits Repeated False Hits Distance Time (s) Bonus

1 21 0 0 11.1 91 2

2 24 0 0 15.6 90 2

3 25 0 0 10.5 97 0

4 24 0 0 11.8 97 1

5 24 0 0 10.7 103 0

6 24 0 0 9.6 94 0

7 22 0 0 11.2 88 1

Average 23.4 0 0 11.5 94 0.86

Results StatisticsResults Statistics

Page 26: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003
Page 27: Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003

17

16

15

14

13

12

11

10

2 (1)1 (22)9

1 (2)8 (14)8

4 (0)7 (16)7

4 (0)5 (17)6

4 (0)9 (13)5

4 (0)4 (18)4

4 (0)4 (18)3

4 (0)2 (20)2

2 (1)3 (19)1

Gender RecognitionFace Detection

17

16

15

14

13

12

11

10

2 (1)1 (22)9

1 (2)8 (14)8

4 (0)7 (16)7

4 (0)5 (17)6

4 (0)9 (13)5

4 (0)4 (18)4

4 (0)4 (18)3

4 (0)2 (20)2

2 (1)3 (19)1

Gender RecognitionFace Detection