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Face Detection – EE368 Group 10 May 30, 2003 1 Face Detection EE 368 Group 10 Waqar Mohsin Noman Ahmed Chung-Tse Mar
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Face Detection – EE368 Group 10 May 30, 2003 2 Overview Project goals Implementation Skin color segmentation Morphological processing Connected region analysis Template matching Female recognition Results
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Face Detection – EE368 Group 10 May 30, 2003 3 Project Goal Detect and locate human faces in color images similar to those from the training set Limited variations in zoom and lighting Similar scene conditions Many occlusions
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Face Detection – EE368 Group 10 May 30, 2003 4 Implementation Overview Skin Color Segmentation Morphological Processing Connected Region Analysis Template Matching Face Coordinates Input Image
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Face Detection – EE368 Group 10 May 30, 2003 5 Skin Color Segmentation Hue Saturation
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Face Detection – EE368 Group 10 May 30, 2003 6 Skin Color Segmentation Non-skin color regions have been eliminated Arms, hands, and various regions still remain
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Face Detection – EE368 Group 10 May 30, 2003 7 Morphological Processing Convert to Grayscale Intensity Thresholding Morphological Opening Fill Holes Mask Image Color-segmented Image Morphological Opening I = rgb2gray(colorSegImage) I(find(I<=50))=0 se=strel(‘disk’,1) I=imopen(I,se) I=imfill(I,’holes’) se=strel(‘disk’,6) I=imopen(I,se)
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Face Detection – EE368 Group 10 May 30, 2003 8 Morphological Processing Before After
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Face Detection – EE368 Group 10 May 30, 2003 9 Connected Region Analysis (Geometry) Reject regions that are Narrow Short Narrow and tall Wide and short Thresholds derived from training image statistics
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Face Detection – EE368 Group 10 May 30, 2003 10 Connected Region Analysis (Euler Number) Reject regions with Euler number greater or equal to 0
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Face Detection – EE368 Group 10 May 30, 2003 11 Result of Connected Region Analysis Before After
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Face Detection – EE368 Group 10 May 30, 2003 12 Template Matching
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Face Detection – EE368 Group 10 May 30, 2003 13 Template Matching
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Face Detection – EE368 Group 10 May 30, 2003 14 Female Face Detection Find the face with the white scarf Draw a box around the face centroid and count the number of white pixels Find the face with the long hair Draw a box around the face centroid and count the number of black pixels The one with the largest number of black or white pixels is designated as a female face
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Face Detection – EE368 Group 10 May 30, 2003 15 Results Training ImageTotal facesDetectedFalse PositiveRepeat Hit 121 00 2242310 3252400 4 00 5 2200 624 00 722 00 TOTAL16416010 Detects 160 out of 164 faces with 1 false positive. Average run- time on a Pentium 4 1.8GHz PC is 35 seconds.
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Face Detection – EE368 Group 10 May 30, 2003 16 Conclusion Face detection program with 97% accuracy over the training images Run-time under a minute Hardest part of project is separating the connected faces Solved with successive template matching and blacking out face regions Not very robust, sensitive to scene conditions in the images
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