GoalsTake any input image and
remove, distort, or cover all human faces
Retain the original integrity of the input image
Step One: Detect Faces
Viola-Jones Object (Face) Detection FrameworkOutlined here – http://www.cs.cmu.edu/~efros/courses/LBMV07/Papers/viola-IJCV-01.pdf
Viola - Jones
Feature types and evaluation:sums of image pixels within rectangular areas four different types of features used in the
framework:
value of any given feature is equal to the sum of the pixels within white rectangles subtracted from the sum of the pixels within dark rectangles
Viola - JonesLearning Algorithm in a standard 24x24 pixel sub-window, there
are 162,336 possible features
the Viola – Jones Algorithm employs a variant of the learning algorithm ‘AdaBoost’ to both select the best features and to train classifiers that use them.
Viola - Jones
For this project, we used the Computer Vision Toolbox Matlab add-on to implement our Facial Detection (highly recommended)
http://www.mathworks.com/products/computer-vision/
Anonymizer
Now that we know that the algorithm is effective at detecting faces, we can find applications for it
One such application is protecting the identities of people in photographs
Anonymizer
We must alter the area of the photograph containing faces
Blurring, covering entirely, or replacing with another image are possible methods