Privacy protecting data collection in media spaces

Around the world as both crime and technology become more prevalent, officials find themselves relying more and more on video surveillance as a cure-all in the name of public safety. Used properly, video cameras help expose wrongdoing but typically come at the cost of privacy to those not involved in any maleficent activity. What if we could design intelligent systems that are more selective in what video they capture, and focus on anomalous events while protecting the privacy of authorized personnel? This paper proposes a novel way of combining sensor technology with traditional video surveillance in building a privacy protecting framework that exploits the strengths of these modalities and complements their individual limitations. Our fully functional system utilizes off the shelf sensor hardware (i.e. RFID, motion detection) for localization, and combines this with a XML-based policy framework for access control to determine violations within the space. This information is fused with video surveillance streams in order to make decisions about how to display the individuals being surveilled. To achieve this, we have implemented several video masking techniques that correspond to varying user privacy levels. These results were achievable in real-time at acceptable frame rates, while meeting our requirements for privacy preservation.