PrivHAR: Recognizing Human Actions from Privacy-preserving Lens


The accelerated use of digital cameras prompts an increasing concern about privacy and security, particularly in applications such as action recognition. In this paper, we propose an optimizing framework to provide robust visual privacy protection along the human action recognition pipeline. Our framework parameterizes the camera lens to successfully degrade the quality of the videos to inhibit privacy attributes and protect against adversarial attacks while maintaining relevant features for activity recognition. We validate our approach with extensive simulations and hardware experiments. See our Project Page!

In 2022 European Conference on Computer Vision
Privacy Preserving Computational Photography Computational Imaging Human Action Recognition Computer Vision
Carlos Hinojosa
Ph.D In Computer Science

I’m Carlos Hinojosa. Computer scientist and engineer with over six years of experience in scientific research and software development. My research interests are in computer vision, machine learning, computational imaging, sparse representation, and signal processing.