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Facial Features Extraction Amit Pillay Ravi Mattani Amit Pillay Ravi Mattani
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What Are We Doing ! Finding Features on a Face Eyes Mouth Nose Finding Features on a Face Eyes Mouth Nose
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Why Facial Feature Extraction? Biometrics Facial recognition system Video Surveillance Human Computer Interface Biometrics Facial recognition system Video Surveillance Human Computer Interface
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Difficulties ! Face Variation Physical characteristic vary Non-uniform lighting Face position Face Variation Physical characteristic vary Non-uniform lighting Face position
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Previous Work. Many Face Extraction Methods Main Trend : Combine image information and knowledge of face Ian-Gang Wang, Eric sung in their article have proposed a morphological procedure to analyze the shape of segmented face region. Several rules have been formulated for the task of locating the contour of the face. Terrillon et al., 1998 mentions the problem of how other body parts such as neck may lead to face localization error Haalick and Shapiro, 1993 demonstrate how morphological operations can simplify the image data while preserving their essential shape characteristics and can eliminate irrelevances. Many Face Extraction Methods Main Trend : Combine image information and knowledge of face Ian-Gang Wang, Eric sung in their article have proposed a morphological procedure to analyze the shape of segmented face region. Several rules have been formulated for the task of locating the contour of the face. Terrillon et al., 1998 mentions the problem of how other body parts such as neck may lead to face localization error Haalick and Shapiro, 1993 demonstrate how morphological operations can simplify the image data while preserving their essential shape characteristics and can eliminate irrelevances.
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Our Process
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Skin Segmentation Depends on color space Used the finding by Yang & Waibel(1995,1996) Normalized r-g color plane. Took seed pixel Classified the pixels based on whether the pixel lies within the threshold Same process carried out for the R and G plane Depends on color space Used the finding by Yang & Waibel(1995,1996) Normalized r-g color plane. Took seed pixel Classified the pixels based on whether the pixel lies within the threshold Same process carried out for the R and G plane
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Skin color segmentation
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Morphological Image Processing Dilation Fills the holes Erosion Restores the shape of the face Dilation Fills the holes Erosion Restores the shape of the face
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Morphological Image Processing
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Skeletonization Reduces binary image objects to a set of thin strokes. Retains important information about the shape of the original object Reduces binary image objects to a set of thin strokes. Retains important information about the shape of the original object
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Skeletonization
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Contour Tracing Certain vertices of these skeleton lines called fitting points can fit the contour of the human face. Certain rules are then applied to deduce these fitting points by analyzing the skeleton lines. Certain vertices of these skeleton lines called fitting points can fit the contour of the human face. Certain rules are then applied to deduce these fitting points by analyzing the skeleton lines.
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Contour Tracing Rule 1 - The contour fitting points should be the vertices of the roughly horizontal skeleton line segments that are long enough. Rule 2 - The left vertex will be selected as candidate for contour fitting if most of the horizontal line segments are positioned at the left of the symmetry axis and vice versa Rule 3 - The contour points should be above a vertical position that is set at 3/4 of the height from the top of the symmetry axis Rule 4 - The point set satisfying the above will be doubled using symmetry axis Rule 1 - The contour fitting points should be the vertices of the roughly horizontal skeleton line segments that are long enough. Rule 2 - The left vertex will be selected as candidate for contour fitting if most of the horizontal line segments are positioned at the left of the symmetry axis and vice versa Rule 3 - The contour points should be above a vertical position that is set at 3/4 of the height from the top of the symmetry axis Rule 4 - The point set satisfying the above will be doubled using symmetry axis
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Contour Tracing
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ROI
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Feature extraction within the ROI Edge Detection using Sobel Operator Vertical position by horizontal integral projection Lip line maximizes the projection Bounded by a rectangular box Same process is repeated for nose and eyes regions within the fixed vertical positions Edge Detection using Sobel Operator Vertical position by horizontal integral projection Lip line maximizes the projection Bounded by a rectangular box Same process is repeated for nose and eyes regions within the fixed vertical positions
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Results
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Conclusion No. of images experimented with = 30 No. of images in which features are correctly identified = 27 Percentage correctly identified = 90 Average time taken to get the output in MATLAB = 15-20 secs No. of images experimented with = 30 No. of images in which features are correctly identified = 27 Percentage correctly identified = 90 Average time taken to get the output in MATLAB = 15-20 secs
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Future Work More robust and dynamic Extended for profile views of image More efficient code for faster execution (applicable especially for MATLAB !!!) More robust and dynamic Extended for profile views of image More efficient code for faster execution (applicable especially for MATLAB !!!)
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References Frontal-view face detection and facial feature extraction using color and morphological operations by Jian-Gang Wang, Eric Sung A Model-Based Gaze Tracking System by Rainer Stiefelhagen, Jie Yang, Alex Waibel Digital Image Processing Using MATLAB by Gonzalez, Woods &Eddins,Prentice Images taken from www.faceresearch.org Prof. Gaborski’s lecture slides www.wikipedia.com Frontal-view face detection and facial feature extraction using color and morphological operations by Jian-Gang Wang, Eric Sung A Model-Based Gaze Tracking System by Rainer Stiefelhagen, Jie Yang, Alex Waibel Digital Image Processing Using MATLAB by Gonzalez, Woods &Eddins,Prentice Images taken from www.faceresearch.org Prof. Gaborski’s lecture slides www.wikipedia.com
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Questions???
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