Deep Learning Approach Protecting Privacy in Camera-Based Critical Applications

• URL: http://arxiv.org/abs/2110.01676v1
• Date: Mon, 4 Oct 2021 19:16:27 GMT
• Title: Deep Learning Approach Protecting Privacy in Camera-Based Critical Applications
• Authors: Gautham Ramajayam, Tao Sun, Chiu C. Tan, Lannan Luo, Haibin Ling
• Abstract summary: We propose a deep learning approach towards protecting privacy in camera-based systems. Our technique distinguishes between salient (visually prominent) and non-salient objects based on the intuition that the latter is unlikely to be needed by the application.
• Score: 57.93313928219855
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Many critical applications rely on cameras to capture video footage for analytical purposes. This has led to concerns about these cameras accidentally capturing more information than is necessary. In this paper, we propose a deep learning approach towards protecting privacy in camera-based systems. Instead of specifying specific objects (e.g. faces) are privacy sensitive, our technique distinguishes between salient (visually prominent) and non-salient objects based on the intuition that the latter is unlikely to be needed by the application.

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