Privacy Implications of Visual
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bernt.schiele(Replace this parenthesis with the @ sign)cispa.saarland
Users today typically share and disseminate massive amounts of visual data (images, videos), via Webpages, social networks, and personal communication. While it is obvious that visual data may contain privacy relevant information and thus (eventually) constitute a threat, there are no systematic methods for assessing that threat. The long-term goal of this project is to provide users with comprehensive and accurate tools for doing just that: Can a user’s activities be extracted from her posted media content? Can a user be re-identified across separate postings? To what extent can an entire user diary and social relations be reconstructed? To design tools capable of answering these questions, we will advance state-of-the-art computer vision techniques to deal with the highly heterogeneous and uncontrolled nature of regular users’ visual data. We will investigate their combination with the context information from social networks, and examine the effect of common protection techniques such as face blurring. We will devise probabilistic models for analyzing the inferences that can be made from a public set of images, and predicting the inferences that could be made (what-if) in case additional images were added.
Role Within the Collaborative Research Center
In the context of this project we are looking for two qualified PhD students with a track record in topics relevant to the project. If you are interested please send a letter of intent together with your short CV to the PIs of the project.