Will future surveillance technology inspire cyberpunk fashion trends?

Will future surveillance technology inspire cyberpunk fashion trends?

Artist and activist Adam Harvey has intensively studied facial recognition software in the hope of understanding how it can be undermined. In his research, Harvey discovered that people can fool facial recognition technology by adapting certain types of fashion trends that make their face asymmetrical and covering certain key areas of the face that these programs are designed to detect.

Ironically, these fashion trends closely resemble those seen in the dystopian "cyberpunk" movies of the 1980s and 1990s. In movies like Blade Runner, for example, the characters are seen with asymmetrical hairstyles and facial makeup Randomly applied These fashion trends can be seen throughout the genre of dystopian science fiction films, and although the reason for this fashion was never explicitly explained, it seems that this may be an aspect of the future that was accurately predicted. Perhaps the characters in your favorite dystopian sci-fi movies looked like a reaction to the surveillance technology that existed in their futuristic worlds.

Harvey's surveillance camouflage tips are based on the OpenCV facial recognition software brand. According to the Harvey website, CV Dazzle:

OpenCV is one of the most used facial detectors. This algorithm works best for images of the front face and excels at the calculation speed. It is ideal for face detection in real time and is widely used in mobile phone applications, web applications, robotics and for scientific research. OpenCV is based on the Viola-Jones algorithm. This video shows the process used by the Viola Jones algorithm, a set of cascading features that scans an image in increasing sizes. By understanding how the algorithm detects a face, the design of a "mask" becomes more intuitive.
fashion trends

The following key elements are also provided here to develop a fashion that will undermine facial recognition software:

1 - Makeup: avoid enhancers: 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 - Nasal bridge: partially obscures the area of ​​the nasal bridge: the region where the nose, eyes and forehead intersect is a key facial feature. This is especially effective against the OpenCV face detection algorithm.

3 - Eyes - Partially darkens one of the eye regions: the position and darkness of the eyes is a key facial feature.

4 - Masks: avoid wearing masks as they are illegal in some cities. Instead of hiding your face, modify the contrast, tonal gradients and spatial relationship of dark and light areas using unique hair, makeup and / or fashion accessories.

5 - Head - The research of Ranran Feng and Balakrishnan Prabhakaran of the University of Texas shows that obscuring the elliptical shape of a head can also improve its ability to block face detection. Link: Facilitate the art of fashion camouflage

6 - Asymmetry: facial recognition algorithms expect symmetry between the left and right sides of the face. By developing an asymmetrical appearance, you can decrease your chance of being detected.

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