Just like other artificial intelligence disciplines, computer vision has (lots of) shortcomings. For example, despite claimed high accuracy of algorithms based on deep learning for face recognition (such as DeepFace by Facebook) there could be times wherein those algorithms could not recognize even simple images. Could you imagine this deficiency was the inspiration for an art project?
Well, two German artists namely Stephan Bogner and Philipp Schmitt have tried exploring the limitations of face recognition algorithms and produce artistic portraits as a byproduct. The project is called Unseen Portraits and it uses OpenCV library to recognize faces while producing artistic photos by manipulating the original images.
The project used two computers; one for distorting the image and one for recognition. Processing and an altered version of MapMap-Vauxhall was used for image distortion. A camera was also used to film the screen that displays distorted images and stream it to the second computer. The second computer applies OpenCV algorithm for face recognition to analyze the video in real time. As you can imagine, the algorithm initially is doing pretty well but as the image is getting distorted more and more, the capability of the software lessens. After a few moments, OpenCV algorithm could no longer recognize the photo anymore. At this very moment, the software will take a screenshot and that is the unseen portrait which is essentially invisible to the computer.
CV Dazzle has also produced a similar project. They investigated how we can conceal ourselves with the help of art in order for us to become invisible to face recognition softwares. They have teamed up with designers and stylists to trick the software. They wanted to discover how fashion could be used to camouflage from the technology of Face recognition.
The name of the CV Dazzle project was derived from the abbreviation of computer vision while Dazzle was used during WWI as a camouflage. CV Dazzle has a goal of breaking apart facial features that produces an Art that makes it unrecognizable in CV algorithms. OpenCV was also used in this project.
The difference on how humans and computers view the world was proved in these projects. The most interesting thing is that human eye (and brain) outperforms computers in recognizing distorted portraits. This fact shows that computer vision still has a lot of potential and space for improvement in the face recognition field.