With the advent of artificial intelligence (AI) and machine learning (ML), customers and the general public have become increasingly aware of their privacy, as well as the value that it holds in today’s data-driven world. Enterprises are actively seeking out and marketing privacy-first solutions, especially in the Computer Vision (CV) domain. They need to reassure their customers that personal information such as faces are anonymized and generally kept safe.
Face blurring is one of the best-known practices when anonymizing both images and videos. It usually involves first detecting the face in an image/video, then applying a blob of pixels or other distortion effects on it. This workload can be considered a CV task. First, we analyze the pixels of the image/video until a face is recognized, then we extract the area where the face is in every frame, and finally we apply a mask on the previously found pixels. The

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