Abstract
Due to the significant increase in various security threats, safety has become a primary concern for our society. As a result, most of the public places such as airports, train stations, banks, shopping malls, subways and streets are nowadays equipped with state-of-the-art multimedia surveillance systems. These systems are meant to process sensory data to automatically detect suspicious or unusual behavior of people and alert security personnel so that preventive actions can be taken. Although such surveillance infrastructure has proved to be very useful from a security perspective; there has been apprehension among people in regard to their privacy safeguards. Citizens have increasingly begun to object to being watched electronically. Hence, there is a need for preserving privacy of people yet providing them a sense of security through effective surveillance. It is worth mentioning that although there has been a significant progress in the field of surveillance research, the issues related to people’s privacy have often been overlooked in the past and have only begun to attract the attention of researchers very recently. The goal of this special issue is to bring forth the recent advances in the privacy research for multimedia surveillance. We received nine submissions from an open call for papers that address different aspects of privacy-aware multimedia surveillance systems. Although many submissions were of good quality, guest editorial committee recommended to accept only five top quality papers after a careful and highly competitive review process. These papers cover diverse issues, including privacy protection using Chaos-cryptography-based data scrambling and Markov chain algorithms, privacy filters in live surveillance video, preserving privacy in mobile video surveillance, and community-based user-specific and location-aware privacy awareness. The first paper of this special issue ‘‘User centric privacy protection in video surveillance’’ by Thomas Winkler and Bernhard Rinner presents a concept for user-centric privacy awareness in video surveillance. The proposed system follows a community-based approach and empowers monitored persons to actively participate in registering cameras using their conventional smart phones. The collected information is used to warn users of violations of their personal privacy policy. Moreover, the proposed system is scalable in terms of different levels of privacy. The second paper ‘‘A general framework for managing and processing live video data with privacy protection’’ by Alexander J. Aved and Kien A. Hua describes the live video database model with an intrinsic privacy model that provides a level of privacy protection not previously available for real-time streaming video data. The authors present the query language LVSQL, the system architecture, the object recognition and cross-camera tracking P. K. Atrey (&) Department of Applied Computer Science, University of Winnipeg, Winnipeg, Canada e-mail: p.atrey@uwinnipeg.ca
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