Triangle-based approach to the detection of human faceSourcePattern Recognition, Vol. 34, Issue 6, June 2001, pp. 1271-1284AuthorsChiun-Hsiun Lin, Kuo-Chin FanSpeakerChia-Chun Wu ()Date2004/11/25

OutlineIntroductionProposed systemPotential face regionsFace verificationExperimentalConclusionsComments

Introduction2 principal parts of the proposed systemPotential face regionsFace verification

Proposed systemPotential facial regionsLabel all 4-connected components and find the center of each blockFind any 3 centers to form a triangleNormalize the size of potential facial regionsVerified by thresholdInput imageDisplay the detection result(60 * 60 pixels)

Frontal view(a)(b)(c)(d)(e)(f)(a) is the original image(b) is the binary image(c) is the isosceles triangle formed by the 3 centers of 3 blocks(e) is the best potential facial region which is normalizedto a standard size (60 * 60 pixels)(f) is the result of the facial detection(d) is the best potential facial region cropped from the binary image that covers the isosceles triangle

Side view(a)(b)(c)(d)(e)(f)

Potential face regionsPixel Tblack values 1Pixel > Twhite values 0For exampleT = 128185 > 128 1

504820018553193178180515456495916517360

0011011100000110

Potential face regionsFor exampleThe center point of Block1

The center point of Block2

Potential face regionsThe isosceles triangle i, j, k. (i

Potential face regionsX1 = X4 = Xi - 1/3*D(i, k), X2 = X3 = Xk + 1/3*D(i, k),Y1 = Y2 = Yi + 1/3*D(i, k), Y3 = Y4 = Yj - 1/3*D(i, k).

Potential face regions(a) The right triangle i, j, k. (i

Potential face regionsX1 = X4 = Xj - 1/6*D(j, k), X2 = X3 = Xj + 1.2*D(j, k),Y1 = Y2 = Yj + 1/4*D(j, k), Y3 = Y4 = Yj - 1.0*D(j, k).X1 = X4 = Xi - 1/6*D(i, j), X2 = X3 = Xi + 1.2*D(i, j),Y1 = Y2 = Yi + 1/4*D(i, j), Y3 = Y4 = Yi - 1.0*D(i, j).

Face verificationMask is formed by 10 binary training faces. For example=Threshold = 5

Face verificationFor all pixelsFor examplePotential facial regionmaskWeight = - 2 - 2 + 6 + 2 + 6 + 6 + 2 + 2 + 2 = 22

001011000

111011000

Face verificationThe threshold of frontal view is 4000~5500.The threshold of side view is 2300~2600.

ExperimentalNeeds about 28 s to locate the correct face position. (200 * 145 pixels)Needs less than 2.5 s to locate the correct face position. (200 * 307 pixels)Experimental results of gray-level images with simple/complex backgrounds

ExperimentalExperimental results of color images with simple/complex backgrounds

ExperimentalVerification of face images with different sizes

ExperimentalVerification of face images with altered lighting conditions

ExperimentalVerification of face images with distinct positions

ExperimentalVerification of face images with changed expressions

ExperimentalVerification of defocus face images

ExperimentalVerification of face images (a) with noise; (b) with partial occlusion of mouth; (c) wearing sunglasses

ExperimentalThe face of a cartoon doll; (b) The face of a Chinese doll

Experimental (error detected)The face is too dark to be detected

Experimental (error detected)The face with right eye being occluded by the black hair

ConclusionsDetect multiple faces in complex backgroundsHandle different sizes, different lighting conditions, varying pose and expression, and noise and defocus problemsPartial shelter and side viewThe minimum size of a face that could be detected is 5 * 5 pixelsThe success rate is approximately 98%.

Comments