Researchers at Catholic University in Leuven, Belgium, have developed a technique of using simple two-dimensional (2D) images to render wearers invisible to surveillance cameras.
The cameras rely on machine learning to identify humans in live video feeds.
The research team experimented with various types of images, but found out that photos of random objects that go through multiple image processing operations were best at tricking machine learning systems into misclassifying a human as something else.
The same system can be modified to mask certain objects from view, if the surveillance system is configured to spot certain objects instead of people.
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA
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