CV Dazzle: Open Source-Camouflage from Face Detection

Schickes Projekt von Adam Harvey an der New York University im Interactive Telecommunication Program: CV Dazzle ist eine Open Source-Tarnung gegen automatische Gesichtserkennung.

CV Dazzle is camouflage from computer vision (CV). It is a form of expressive interference that combines makeup and hair styling (or other modifications) with face-detection thwarting designs. The name is derived from a type of camouflage used during WWI, called Dazzle, which was used to break apart the gestalt-image of warships, making it hard to discern their directionality, size, and orientation. Likewise, the goal of CV Dazzle is to break apart the gestalt of a face, or object, and make it undetectable to computer vision algorithms, in particular face detection.

And because face detection is the first step in automated facial recognition, CV Dazzle can be used in any environment where automated face recognition systems are in use, such as Google's Picasa, Flickr, or FaceBook.

(Vimeo Direktface, Danke Anonymous!)

This video visualizes the detection process of OpenCV's face detector. The algorithm uses the Viola Jones method of calculating the integral image and then performing some calculations on all the areas defined by the black and white rectangles to analyze the differences between the dark and light regions of a face. The sub-window (in red) is scanned across the image at various scales to detect if there is a potential face within the window. If not, it continues scanning. If it passes all stages in the cascade file, it is marked with a red rectangle. But this does not yet confirm a face. In the post-processing stage all the potential faces are checked for overlaps. Typically, 2 or 3 overlapping rectangles are required to confirm a face. Loner rectangles are rejected as false-positives.