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Automated Face Detection System

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Abhiroop Ghatak
Abhiroop Ghatak

Presentation about the project of face detection automation .

1 of 31
openCV based image processed attendence system 1.abhiroop ghatak 2. rohit verma 3. sunny Jain 4. vivek mittal Under the guidance of Sangeetha jaganathan ,[object Object],1. rohit verma 2. sunny Jain 3. vivek mittal 4. abhiroop ghatak
Problem Statement ,[object Object],[object Object]
System steps
Intro. to openCV ,[object Object]
[object Object]
Applications www.viisage.com  Access Control www.visionics.com
Features ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Modules ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why is Managing OpenCV Objects Important ? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How Does OpenCV Represent Images? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Handling IplImage ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Creating an IplImage ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Destroying an IplImage ,[object Object],[object Object]
Utilizing IplImage ,[object Object],[object Object],[object Object],[object Object],Setting the Region of Interest (ROI ) Setting the ROI of the image allows the user to select a rectangular region of the image to work with. This is useful after localizing objects for extraction and further processing. While the region is set the rest of the image will be ignored. Meaning any operation directed on the image will act on only the region (including cvShowImage ). ,[object Object],[object Object],Setting the Channel of Interest (COI ) Setting the channel of the image allows the user to work with a particular layer of the image. i.e. The ‘R’ layer of an RGB image or the ‘V’ layer in the HSV format. NOTE: Not all OpenCV functions support this.
Other Static Array Types ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Face detection Face recognition
[object Object],[object Object],[object Object],[object Object],what is object detection ?
[object Object],[object Object],[object Object],Resize image Image Contrast stretching Face Detection Faces Non-faces Transform to integral images
Paul Viola and Michael Jones technique ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Viola-Jones Technique(contd..) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Features ,[object Object],[object Object],[object Object],[object Object]
Feature Extraction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Face Detection Algorithm Face Localization Lighting Compensation Skin Color Detection Color Space Transformation Variance-based Segmentation Connected Component & Grouping Face Boundary Detection Verifying/ Weighting Eyes-Mouth Triangles Eye/ Mouth Detection Facial Feature Detection Input Image Output Image
Face Recognition Problem Statement Identify a person’s face image from face database. Applications Human-Computer interface, Static matching of photographs, Video surveillance, Biometric security, Image and film processing.
Challenges ,[object Object],[object Object],[object Object],[object Object]
Inter-class Similarity ,[object Object],Twins Father and son www.marykateandashley.com news.bbc.co.uk/hi/english/in_depth/americas/2000/us_elections
Intra-class Variability ,[object Object]
Face Recognition Using Eigenfaces
[object Object],[object Object],Eigen Space and Eigen Faces
Principal Component Analysis (PCA) For a set M of N-dimensional vectors {x 1 , x 2 …x M } , PCA finds the eigenvalues and eigenvectors of the covariance matrix of the vectors  - the average of the image vectors an image as 1d vector u k - Eigenvectors  k - Eigenvalues Keep only k eigenvectors, corresponding to the k largest eigenvalues.
Method of Eigenfaces ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
References.. ,[object Object],[object Object],[object Object]
Questions? ,[object Object],[object Object],[object Object]

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Automated Face Detection System

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  • 6. Applications www.viisage.com  Access Control www.visionics.com
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  • 14. Face detection Face recognition
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  • 21. Face Detection Algorithm Face Localization Lighting Compensation Skin Color Detection Color Space Transformation Variance-based Segmentation Connected Component & Grouping Face Boundary Detection Verifying/ Weighting Eyes-Mouth Triangles Eye/ Mouth Detection Facial Feature Detection Input Image Output Image
  • 22. Face Recognition Problem Statement Identify a person’s face image from face database. Applications Human-Computer interface, Static matching of photographs, Video surveillance, Biometric security, Image and film processing.
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  • 28. Principal Component Analysis (PCA) For a set M of N-dimensional vectors {x 1 , x 2 …x M } , PCA finds the eigenvalues and eigenvectors of the covariance matrix of the vectors  - the average of the image vectors an image as 1d vector u k - Eigenvectors  k - Eigenvalues Keep only k eigenvectors, corresponding to the k largest eigenvalues.
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Editor's Notes

  1. O O Face recognition can be categorized into appearance-based, geometry-based, and hybrid approaches.
  2. O O Face recognition can be categorized into appearance-based, geometry-based, and hybrid approaches.
  3. O O Face recognition can be categorized into appearance-based, geometry-based, and hybrid approaches.