Visual privacy is the relationship between collection and dissemination of visual information, the expectation of privacy, and the legal issues surrounding them. These days digital cameras are ubiquitous. They are one of the most common sensors found in electronic devices, ranging from smartphones to tablets, and laptops to surveillance cams. However, privacy and trust implications surrounding it limit its ability to seamlessly blend into computing environment. In particular, large-scale camera networks have created increasing interest in understanding the advantages and disadvantages of such deployments. It is estimated that over 4 million CCTV cameras deployed in the UK.[1] Due to increasing security concerns, camera networks have continued to proliferate across other countries such as the United States. While the impact of such systems continues to be evaluated, in parallel, tools for controlling how these camera networks are used and modifications to the images and video sent to end-users have been explored.
Many different forms of technologies are explored to preserve privacy while providing information collected from camera networks. Most of these solutions rely upon the target application and try to accomplish it in a privacy-preserving manner:
"Respectful Cameras" is a solution that automatically obscures the faces of observed people in video by overlaying a colored dot over the face of the individual. This technology tracks colored markers, worn by individuals, and then infers the location of a face by an offset from the marker.[2]
Google Streetview uses automatic face-detection to blur all faces in the city of Manhattan.[3]
Eptascape has a product which provides automatic people tracking and provides privacy-enabled surveillance.[4]
Cardea is a context-aware visual privacy protection mechanism that protects bystanders' visual privacy in photos according to their context-dependent privacy preferences, using face recognition and context computing techniques.[5]
Privacy-preserving Lens design [7] consists of the joint optimization of optics and algorithms to perform vision tasks like human pose estimation and action recognition.
Visual privacy hence encompasses privacy aware and privacy preserving systems which factor in the compute design choices,[8] privacy policies regarding data-sharing in a collaborative and distributive environment and data ownership itself. At times privacy and trust are interlinked especially for the adoption and wide-scale acceptance of any technology. Having a fair and accurate computer vision model goes a long way into ensuring the prior two. A lot of developers are also now inculcating perspectives from Privacy by design. These include but are not limited to processing all user sensitive data on the edge client device, decreasing data retentivity, and ensuring that the data is not used for anything it is not intended for.
Referencesedit
^McCahill, M. and Norris, C. 2004, From cameras to control rooms: the mediation of the image by cctv operatives, CCTV and Social Control: The politics and practice of video surveillance-European and global perspectives, 2004
^Jeremy Schiff; Marci Meingast; Deirdre K. Mulligan; Shankar Sastry; Ken Goldberg (2007). "Respectful Cameras: Detecting Visual Markers in Real-Time to Address Privacy Concerns". International Conference on Intelligent Robots and Systems (IROS). San Diego, California. October 2007.
^. www.eptascape.com. Archived from the original on 21 June 2008. Retrieved 13 January 2022.
^(PDF). Archived from the original (PDF) on 2018-11-08. Retrieved 2023-12-24.
^Pittaluga, Francesco; Koppal, Sanjeev J. (June 2015). "Privacy preserving optics for miniature vision sensors". 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Boston, MA, USA: IEEE. pp. 314–324. CiteSeerX10.1.1.944.2193. doi:10.1109/CVPR.2015.7298628. ISBN9781467369640. S2CID 14056410.
^Hinojosa, Carlos; Niebles, Juan Carlos; Arguello, Henry (October 2021). "Learning Privacy-preserving Optics for Human Pose Estimation". 2021 IEEE International Conference on Computer Vision (ICCV). Virtual, USA: IEEE/CVF: 2573–2582.
^Koelle, Marion; Wolf, Katrin; Boll, Susanne (2018). "Beyond LED Status Lights - Design Requirements of Privacy Notices for Body-worn Cameras". Proceedings of the Twelfth International Conference on Tangible, Embedded, and Embodied Interaction. Tei '18. Stockholm, Sweden: ACM Press. pp. 177–187. doi:10.1145/3173225.3173234. ISBN9781450355681. S2CID 3954480.
External linksedit
Unblinking: New Perspectives on Visual Privacy in the 21st Century
January 01, 1970
visual, privacy, this, article, possibly, contains, original, research, please, improve, verifying, claims, made, adding, inline, citations, statements, consisting, only, original, research, should, removed, june, 2008, learn, when, remove, this, message, rela. This article possibly contains original research Please improve it by verifying the claims made and adding inline citations Statements consisting only of original research should be removed June 2008 Learn how and when to remove this message Visual privacy is the relationship between collection and dissemination of visual information the expectation of privacy and the legal issues surrounding them These days digital cameras are ubiquitous They are one of the most common sensors found in electronic devices ranging from smartphones to tablets and laptops to surveillance cams However privacy and trust implications surrounding it limit its ability to seamlessly blend into computing environment In particular large scale camera networks have created increasing interest in understanding the advantages and disadvantages of such deployments It is estimated that over 4 million CCTV cameras deployed in the UK 1 Due to increasing security concerns camera networks have continued to proliferate across other countries such as the United States While the impact of such systems continues to be evaluated in parallel tools for controlling how these camera networks are used and modifications to the images and video sent to end users have been explored Contents 1 Technologies 1 1 Forms of Visual Data 1 2 Systems 2 References 3 External linksTechnologies editTo enhance visual privacy a number of different technologies have been suggested Forms of Visual Data edit Visual Privacy is often typically applied to particular technologies including Closed circuit television CCTVs Visual sensor network Also referred to as Camera Networks Camera phone Smart homes Systems edit Many different forms of technologies are explored to preserve privacy while providing information collected from camera networks Most of these solutions rely upon the target application and try to accomplish it in a privacy preserving manner Respectful Cameras is a solution that automatically obscures the faces of observed people in video by overlaying a colored dot over the face of the individual This technology tracks colored markers worn by individuals and then infers the location of a face by an offset from the marker 2 Google Streetview uses automatic face detection to blur all faces in the city of Manhattan 3 Eptascape has a product which provides automatic people tracking and provides privacy enabled surveillance 4 Cardea is a context aware visual privacy protection mechanism that protects bystanders visual privacy in photos according to their context dependent privacy preferences using face recognition and context computing techniques 5 Thermal and depth cameras 6 are used in person detection and people counting Privacy preserving Lens design 7 consists of the joint optimization of optics and algorithms to perform vision tasks like human pose estimation and action recognition Visual privacy hence encompasses privacy aware and privacy preserving systems which factor in the compute design choices 8 privacy policies regarding data sharing in a collaborative and distributive environment and data ownership itself At times privacy and trust are interlinked especially for the adoption and wide scale acceptance of any technology Having a fair and accurate computer vision model goes a long way into ensuring the prior two A lot of developers are also now inculcating perspectives from Privacy by design These include but are not limited to processing all user sensitive data on the edge client device decreasing data retentivity and ensuring that the data is not used for anything it is not intended for References edit McCahill M and Norris C 2004 From cameras to control rooms the mediation of the image by cctv operatives CCTV and Social Control The politics and practice of video surveillance European and global perspectives 2004 Jeremy Schiff Marci Meingast Deirdre K Mulligan Shankar Sastry Ken Goldberg 2007 Respectful Cameras Detecting Visual Markers in Real Time to Address Privacy Concerns International Conference on Intelligent Robots and Systems IROS San Diego California October 2007 Street View revisits Manhattan Eptascape Inc MPEG 7 Video Analytics www eptascape com Archived from the original on 21 June 2008 Retrieved 13 January 2022 Cardea Context Aware Visual Privacy Protection for Photo Taking and Sharing PDF Archived from the original PDF on 2018 11 08 Retrieved 2023 12 24 Pittaluga Francesco Koppal Sanjeev J June 2015 Privacy preserving optics for miniature vision sensors 2015 IEEE Conference on Computer Vision and Pattern Recognition CVPR Boston MA USA IEEE pp 314 324 CiteSeerX 10 1 1 944 2193 doi 10 1109 CVPR 2015 7298628 ISBN 9781467369640 S2CID 14056410 Hinojosa Carlos Niebles Juan Carlos Arguello Henry October 2021 Learning Privacy preserving Optics for Human Pose Estimation 2021 IEEE International Conference on Computer Vision ICCV Virtual USA IEEE CVF 2573 2582 Koelle Marion Wolf Katrin Boll Susanne 2018 Beyond LED Status Lights Design Requirements of Privacy Notices for Body worn Cameras Proceedings of the Twelfth International Conference on Tangible Embedded and Embodied Interaction Tei 18 Stockholm Sweden ACM Press pp 177 187 doi 10 1145 3173225 3173234 ISBN 9781450355681 S2CID 3954480 External links editUnblinking New Perspectives on Visual Privacy in the 21st Century Retrieved from https en wikipedia org w index php title Visual privacy amp oldid 1191610113, wikipedia, wiki, book, books, library,
