Artist wants to undermine surveillance technology with cyber punk fashion
Artist and activist Adam Harvey has intensively studied facial recognition software with the hopes of understanding how it can be undermined. In his research, Harvey has discovered that people can trick facial recognition technology by adapting certain types of fashion trends that make their face asymmetrical and by covering certain key areas of the face that these programs are designed to detect.
Ironically, these fashion trends look a lot like those seen in the dystopian “cyber-punk” films of the 1980’s and 1990’s. In films like Blade Runner for example, characters are seen with asymmetrical hairstyles and randomly applied facial make up. These fashion trends can be seen throughout the whole genre of dystopian science fiction movies, and although the reason for this fashion was never explicitly explained, it seems that this may be one aspect of the future that was predicted accurately. Perhaps the characters in your favorite dystopian science fiction movies looked the way that they did as a reaction to the surveillance technology that existed in their futuristic worlds.
Harvey’s surveillance camouflage tips are based off of the OpenCV brand of facial recognition software. According to Harvey’s website CV Dazzle:
OpenCV is one of the most widely used face detectors. This algorithm performs best for frontal face imagery and excels at computational speed. It’s ideal for real-time face detection and is used widely in mobile phone apps, web apps, robotics, and for scientific research. OpenCV is based on the the Viola-Jones algorithm. This video shows the process used by the Viola Jones algorithm, a cascading set of features that scans across an image at increasing sizes. By understanding how the algorithm detects a face, the process of designing an “anti-face” becomes more intuitive.
Harvey also provides the following key elements in developing a fashion that will undermine facial recognition software:
1 – Makeup- Avoid enhancers: They amplify key facial features. This makes your face easier to detect. Instead apply makeup that contrasts with your skin tone in unusual tones and directions: light colors on dark skin, dark colors on light skin.
2 – Nose Bridge – Partially obscure the nose-bridge area: The region where the nose, eyes, and forehead intersect is a key facial feature. This is especially effective against OpenCV’s face detection algorithm.
3 – Eyes – Partially obscure one of the ocular regions: The position and darkness of eyes is a key facial feature.
4 – Masks – Avoid wearing masks as they are illegal in some cities. Instead of concealing your face, modify the contrast, tonal gradients, and spatial relationship of dark and light areas using hair, makeup, and/or unique fashion accessories.
5 – Head – Research from Ranran Feng and Balakrishnan Prabhakaran at University of Texas, shows that obscuring the elliptical shape of a head can also improve your ability to block face detection. Link: Facilitating fashion camouflage art
6 – Asymmetry – Facial-recognition algorithms expect symmetry between the left and right sides of the face. By developing an asymmetrical look, you may decrease your probability of being detected.
Below are some of the looks suggested by CV Dazzle. How do they compare with characters from your favorite science fiction film?
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