Face Detection Using Color Thresholding and

Eigenimage Template Matching

Diederik MariusSumita Pennathur

Klint Rose

Approach

Input Image

YCbCrThresholding

Binary ImageProcessing

Separationof “Blobs”

SizeThreshold

Homogeneity/Aspect Ratio

ThresholdCross-covariancewith Eigenimage

DuplicateDetectionRemoval

Rejection

Match Face Location to Input Image

Indi

vidu

al b

lobs

x10

Skin Segmentation Used distribution of Cr and Cb

values for faces vs. background to thresholdSkin region: 105<Cr<135

140<Cb<165

Binary Image Processing Erosion and dilation with face-shaped

segmentation element Removes small foreground and

background objects Delineates between larger regions

Separation and Rejection Larger regions labeled and

separated Series of Rejection Thresholding:

Size of regions (>3000 total pixels) Aspect Ratio (0.5 <AR< 1.8 ) St. Dev. of image values (60<<100)

Size based thresholding

Coupled AR and St. Dev. based thresholdin

g

Eigenimages Computed from set of “good” faces Employed Sirovich-Kirby method to calculate first 10 eigenimages Eigenimage #2: most accurate location of center of face Used eigenimage #2 exclusively

1 2 3 4 5 6 7 8 9 10

Template Matching Found cross-covariance peak and

marked as potential center Removed face sized area from

image Found new highest peak - repeated

10x

False Detection Removal Thresholded detected peaks

to obtain potential faces only Determined whether

multiple peaks belong to the same person (neck, etc)

Rejection criteria: Near the same y-axis and within a predetermined vertical distance of a previous point

Rejectedpoints

Typical Detection Result Detection problems: rotated faces,

small faces, hands, faces in lower 1/3

Results Average run time: 100 seconds 95% of faces found 4.4% false positives

# Faces # Correct False Pos False Neg % Correct % FalseTraining Image 1 21 21 1 0 100 4.8Training Image 2 23 21 5 2 91 21.7Training Image 3 23 22 0 1 96 0.0Training Image 4 24 22 0 2 92 0.0Training Image 5 24 23 0 1 96 0.0Training Image 6 24 23 0 1 96 0.0Training Image 7 22 19 1 3 86 4.5Total 161 151 7 10 95 4.4

17

16

5 (0)4 (19)15

5 (0)4 (19)14

5 (0)4 (19)13

5 (0)4 (19)12

5 (0)15 (08)11

2 (1)2 (20)10

2 (1)1 (22)9

1 (2)13 (14)8

5 (0)12 (16)7

5 (0)11 (17)6

5 (0)14 (13)5

5 (0)9 (18)4

5 (0)9 (18)3

5 (0)2 (20)2

2 (1)4 (19)1

Gender RecognitionFace Detection

17

16

5 (0)4 (19)15

5 (0)4 (19)14

5 (0)4 (19)13

5 (0)4 (19)12

5 (0)15 (08)11

2 (1)2 (20)10

2 (1)1 (22)9

1 (2)13 (14)8

5 (0)12 (16)7

5 (0)11 (17)6

5 (0)14 (13)5

5 (0)9 (18)4

5 (0)9 (18)3

5 (0)2 (20)2

2 (1)4 (19)1

Gender RecognitionFace Detection