Camouflage against Face Detection Recognition Algorithms

Not that any of you could find a purpose for this

The algorithm looks at the image (or video) and tries to match the Haar features (in black and white) to features of the image. The more features match, the more likely it is that the image contains a face. As its name implies, a cascade is made of a series of feature-tests. For a face to be detected, the algorithm must match a cascade or series of features in the expected locations. The examples above and below show the Haar features from the cascade files that ship with OpenCV. For more information on how face detection works, I recommend starting with a 2007 article from Servo magazine about how face detection works.

Full link and info

Preliminary makeup patterns to hide from face detection

About this image:
• Images with a red square tested positive, a face was found
• Images without a red square tested negative, no face was found
• Images under the section “TEST PATTERNS” are made according to results of the Haar deconstruction
• Images under “RANDOM PATTERNS” are random doodles made without the anti-face detection patterns in mind
• Images underneath the “NO PATTERNS” heading are left untouched to show that the face detection works well on simple line drawings
• Line drawings are from Figure Drawing for Fashion Design
  

Via io9.