1,566 research outputs found

    Scrambling for Privacy Protection in Video Surveillance Systems

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    In this paper, we address the problem of privacy protection in video surveillance. We introduce two efficient approaches to conceal Regions of Interest (ROI) based on transform-domain or codestream-domain scrambling. In the first technique, the sign of selected transform coefficients is pseudo-randomly flipped during encoding. In the second method, some bits of the codestream are pseudo-randomly inverted. We address more specifically the cases of MPEG-4 as it is today the prevailing standard in video surveillance equipment. Simulations show that both techniques successfully hide private data in ROI while the scene remains comprehensible. Additionally, the amount of noise introduced by the scrambling process can be adjusted. Finally, the impact on coding efficiency performance is small and the required computational complexity is negligible

    Towards optimal distortion-based visual privacy filters

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    The widespread usage of digital video surveillance systems has increased the concerns for privacy violation. Since video surveillance systems are invasive, it is a challenge to find an acceptable balance between privacy of the public under surveillance and security related features of the systems. Many privacy protection tools have been proposed for preserving privacy, ranging from such simple methods like blurring or pixelization to more advanced like scrambling and geometrical transform based filters. However, for a given filter implemented in a practical video surveillance system, it is necessary to know the strength with which the filter should be applied to protect privacy reliably. Assuming an automated surveillance system, this paper objectively investigates several privacy protection filters with varying strength degrees and determines their optimal strength values to achieve privacy protection. To this end, five privacy filters were applied to images from FERET dataset and the performance of three recognition algorithms was evaluated. The results show that different privacy protection filters influence the accuracy of different versions of face recognition differently and this influence depends both on the robustness of the recognition and the type of distortion filter

    Privacy region protection for H.264/AVC with enhanced scrambling effect and a low bitrate overhead

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    While video surveillance systems have become ubiquitous in our daily lives, they have introduced concerns over privacy invasion. Recent research to address these privacy issues includes a focus on privacy region protection, whereby existing video scrambling techniques are applied to specific regions of interest (ROI) in a video while the background is left unchanged. Most previous work in this area has only focussed on encrypting the sign bits of nonzero coefficients in the privacy region, which produces a relatively weak scrambling effect. In this paper, to enhance the scrambling effect for privacy protection, it is proposed to encrypt the intra prediction modes (IPM) in addition to the sign bits of nonzero coefficients (SNC) within the privacy region. A major issue with utilising encryption of IPM is that drift error is introduced outside the region of interest. Therefore, a re-encoding method, which is integrated with the encryption of IPM, is also proposed to remove drift error. Compared with a previous technique that uses encryption of IPM, the proposed re-encoding method offers savings in the bitrate overhead while completely removing the drift error. Experimental results and analysis based on H.264/AVC were carried out to verify the effectiveness of the proposed methods. In addition, a spiral binary mask mechanism is proposed that can reduce the bitrate overhead incurred by flagging the position of the privacy region. A definition of the syntax structure for the spiral binary mask is given. As a result of the proposed techniques, the privacy regions in a video sequence can be effectively protected by the enhanced scrambling effect with no drift error and a lower bitrate overhead.N/

    An intelligent real-time occupancy monitoring system with enhanced encryption and privacy

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    Visual Privacy Protection Methods: A Survey

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    Recent advances in computer vision technologies have made possible the development of intelligent monitoring systems for video surveillance and ambient-assisted living. By using this technology, these systems are able to automatically interpret visual data from the environment and perform tasks that would have been unthinkable years ago. These achievements represent a radical improvement but they also suppose a new threat to individual’s privacy. The new capabilities of such systems give them the ability to collect and index a huge amount of private information about each individual. Next-generation systems have to solve this issue in order to obtain the users’ acceptance. Therefore, there is a need for mechanisms or tools to protect and preserve people’s privacy. This paper seeks to clarify how privacy can be protected in imagery data, so as a main contribution a comprehensive classification of the protection methods for visual privacy as well as an up-to-date review of them are provided. A survey of the existing privacy-aware intelligent monitoring systems and a valuable discussion of important aspects of visual privacy are also provided.This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02) and by the European Commission under project “caring4U - A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010-274649). José Ramón Padilla López and Alexandros Andre Chaaraoui acknowledge financial support by the Conselleria d'Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2012/064 and ACIF/2011/160 respectively)

    Anonymous subject identification and privacy information management in video surveillance

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    The widespread deployment of surveillance cameras has raised serious privacy concerns, and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. Of equal importance are the privacy and efficiency of techniques to first, identify those individuals for privacy protection and second, provide access to original surveillance video contents for security analysis. In this paper, we propose an anonymous subject identification and privacy data management system to be used in privacy-aware video surveillance. The anonymous subject identification system uses iris patterns to identify individuals for privacy protection. Anonymity of the iris-matching process is guaranteed through the use of a garbled-circuit (GC)-based iris matching protocol. A novel GC complexity reduction scheme is proposed by simplifying the iris masking process in the protocol. A user-centric privacy information management system is also proposed that allows subjects to anonymously access their privacy information via their iris patterns. The system is composed of two encrypted-domain protocols: The privacy information encryption protocol encrypts the original video records using the iris pattern acquired during the subject identification phase; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of our framework
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