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The growing popularity of mobile and wearable devices with built-in cameras,the bright prospect of camera related applications such as augmented realityand life-logging system, the increased ease of taking and sharing photos, andadvances in computer vision techniques have greatly facilitated people's livesin many aspects, but have also inevitably raised people's concerns about visualprivacy at the same time. Motivated by recent user studies that people'sprivacy concerns are dependent on the context, in this paper, we proposeCardea, a context-aware and interactive visual privacy protection frameworkthat enforces privacy protection according to people's privacy preferences. Theframework provides people with fine-grained visual privacy protection using: i)personal privacy profiles, with which people can define their context-dependentprivacy preferences; and ii) visual indicators: face features, for devices toautomatically locate individuals who request privacy protection; and iii) handgestures, for people to flexibly interact with cameras to temporarily changetheir privacy preferences. We design and implement the framework consisting ofthe client app on Android devices and the cloud server. Our evaluation resultsconfirm this framework is practical and effective with 86% overall accuracy,showing promising future for context-aware visual privacy protection frompervasive cameras.

Cardea: Context-Aware Visual Privacy Protection from Pervasive Cameras