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Many critical applications rely on cameras to capture video footage foranalytical purposes. This has led to concerns about these cameras accidentallycapturing more information than is necessary. In this paper, we propose a deeplearning approach towards protecting privacy in camera-based systems. Insteadof specifying specific objects (e.g. faces) are privacy sensitive, ourtechnique distinguishes between salient (visually prominent) and non-salientobjects based on the intuition that the latter is unlikely to be needed by theapplication.

Deep Learning Approach Protecting Privacy in Camera-Based Critical Applications