The effects of filtered video on awareness and privacy
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Proceedings of the ACM 2nd international workshop on Video surveillance & sensor networks
Privacy protecting data collection in media spaces
Proceedings of the 12th annual ACM international conference on Multimedia
Enabling Video Privacy through Computer Vision
IEEE Security and Privacy
Access control, confidentiality and privacy for video surveillance databases
Proceedings of the eleventh ACM symposium on Access control models and technologies
Factors on the sense of privacy in video surveillance
Proceedings of the 3rd ACM workshop on Continuous archival and retrival of personal experences
Dynamic privacy assessment in a smart house environment using multimodal sensing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Privacy in video surveilled areas
Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services
Object-Video Streams for Preserving Privacy in Video Surveillance
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Study of subjective and objective quality assessment of video
IEEE Transactions on Image Processing
Video data hiding for managing privacy information in surveillance systems
EURASIP Journal on Information Security - Special issue on enhancing privacy protection in multimedia systems
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
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Privacy is a big concern in current video surveillance systems. Due to privacy issues, many strategic places remain unmonitored leading to security threats. The main problem with existing privacy protection methods is that they assume availability of accurate region of interest (RoI) detectors that can detect and hide the privacy sensitive regions such as faces. However, the current detectors are not fully reliable, leading to breaches in privacy protection. In this paper, we propose a privacy protection method that adopts adaptive data transformation involving the use of selective obfuscation and global operations to provide robust privacy even with unreliable detectors. Further, there are many implicit privacy leakage channels that have not been considered by researchers for privacy protection. We block both implicit and explicit channels of privacy leakage. Experimental results show that the proposed method incurs 38% less distortion of the information needed for surveillance in comparison to earlier methods of global transformation; while still providing near-zero privacy loss.