Bringing together an interdisciplinary team from journalism, computer science, cognitive science, fine art and anthropology, we have researched and created a wholly new technique to anonymize interview subjects and scenes in regular and 360 video. Our goal was to create a working technique that would be much better at conveying emotional and knowledge information than current anonymization techniques. We first researched the best techniques used today — which generally are able to pixelate the face using facial awareness (a moving area that senses the face and pixelates only that area). Based on our expertise and research we have created an updated (v.3) technique using an AI painterly approach to anonymization.

When painting your portrait, artists attempt to convey the sitter’s outer and inner resemblance (outer how they look, inner who they are). Our research work has been to use more than 100 years of artist technique but to lower outer resemblance (what someone outwardly looks like) while keep as high as possible a subjects inner resemblance (what they are conveying, how they are feeling). Our v.3 system uses several levels of AI processing to simulate a smart painter using art abstraction techniques to repaint the regular or 360 video as if an artist was painting every frame. It should be noted that our multistage AI art process is not an image processing process — it does not change the pixels of the frames of the source regular or 360 video (as you might do in an Adobe product). Instead, it specially paints a painting style result of every frame of the video. It is an open and dynamic process, allowing levels of control throughout. It is our eventual goal that either the interviewee or documentary producer can use options in the system to customize the final result based on their wants and needs.

Our goals have been two fold: to assess the effectiveness of AI anonymized video at retaining emotional resonance of content and to develop this tool into a production-ready platform for newsrooms and documentarians working in 360 and VR. We have succeeded through our preliminary study in determining the effectiveness of the AI-driven abstraction and are now ready to proceed with further full study and public-facing projects utilizing the technology.

The impact of this work will be shown through our first collaboration with our media/newsroom partner where we are able to more thoroughly field test the technology in a production setting. We believe the effectiveness of the tool at anonymizing while retaining a strong degree of emotional connection or resonance will be invaluable in a production workflow and will lead to a better final product when it comes to anonymized video, especially in 360 or VR.