Visual privacy

<h2 id="forms-of-visual-data">Forms of Visual Data</h2>
<p>Visual Privacy is often typically applied to particular technologies including:
</p>
<ul><li><a href="/facts/Closed-circuit_television/1JCtvSmx">Closed-circuit television</a> (CCTVs)</li>
<li><a href="/facts/Visual_sensor_network/bP9xfo2r">Visual sensor network</a> (Also referred to as Camera Networks)</li>
<li><a href="/facts/Camera_phone/EzCfpkdl">Camera phone</a></li>
<li><a href="/facts/Home_automation/kfz6C07m">Smart homes</a></li></ul>
<h2 id="technologies-enhancing-visual-privacy">Technologies enhancing visual privacy</h2>
<p>Different forms of technologies are explored to enhance or 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:
</p>
<ul><li>"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.<a class="footnote-ref" id="fnref:2" href="#fn:2"><sup>2</sup></a></li>
<li><a href="/facts/Google_Streetview/Ruqzal5A">Google Streetview</a> uses automatic <a href="/facts/Face_detection/KVIvPRFA">face detection</a> to blur all faces in the city of Manhattan.<a class="footnote-ref" id="fnref:3" href="#fn:3"><sup>3</sup></a></li>
<li>Eptascape has a product which provides automatic <a href="/facts/People_tracking/4fKPC7Fp">people tracking</a> and provides privacy-enabled surveillance.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a></li>
<li>Cardea is a context-aware visual privacy protection mechanism that protects bystanders' visual privacy in photos according to their context-dependent privacy preferences, using <a href="/facts/Face_recognition/mtVxaDln">face recognition</a> and <a href="/facts/Context_computing/eIBhIMak">context computing</a> techniques.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a></li>
<li><a href="/facts/Thermal_camera/dplJK39u">Thermal</a> and <a href="/facts/Depth_camera/MSySNrR1">depth cameras</a><a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a> are used in person detection and people counting.</li>
<li>Privacy-preserving Lens design<a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a> consists of the joint optimization of optics and algorithms to perform vision tasks like human pose estimation and action recognition.</li></ul>
<p>Visual privacy hence encompasses privacy aware and privacy preserving systems which factor in the compute design choices,<a class="footnote-ref" id="fnref:8" href="#fn:8"><sup>8</sup></a> 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 <a href="/facts/Computer_vision/Tl2Yyk66">computer vision</a> model goes a long way into ensuring the prior two. A lot of developers are also now inculcating perspectives from <a href="/facts/Privacy_by_design/A1DKL4PP">privacy by design</a>. 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.
</p>
<h2 id="see-also">See also</h2>
<ul><li><a href="/facts/Mass_surveillance/GgAEJtso">Mass surveillance</a></li></ul>

<h2 id="external-links">External links</h2>
<ul><li><a href="https://www.law.berkeley.edu/institutes/bclt/events/unblinking/unblink.html">Unblinking: New Perspectives on Visual Privacy in the 21st Century</a></li></ul>

<h2 id="references">References</h2>

<ol>
<li id="fn:1"><p>"How Many CCTV Cameras in London? UK CCTV Numbers (Updated 2022)". Clarion UK. 2022-10-04. Retrieved 2024-06-18. <a href="https://clarionuk.com/resources/how-many-cctv-cameras-are-in-london/" target="_blank">https://clarionuk.com/resources/how-many-cctv-cameras-are-in-london/</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li>
<li id="fn:2"><p>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. <a href="http://www.cs.berkeley.edu/~jschiff/RespectfulCameras/index.html" target="_blank">http://www.cs.berkeley.edu/~jschiff/RespectfulCameras/index.html</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li>
<li id="fn:3"><p>"Street View revisits Manhattan". <a href="http://google-latlong.blogspot.com/2008/05/street-view-revisits-manhattan.html" target="_blank">http://google-latlong.blogspot.com/2008/05/street-view-revisits-manhattan.html</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li>
<li id="fn:4"><p>"Eptascape, Inc. MPEG-7 Video Analytics". www.eptascape.com. Archived from the original on 21 June 2008. Retrieved 13 January 2022. <a href="https://web.archive.org/web/20080621124054/http://www.eptascape.com/" target="_blank">https://web.archive.org/web/20080621124054/http://www.eptascape.com/</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li>
<li id="fn:5"><p>"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. <a href="https://web.archive.org/web/20181108184408/https://home.cse.ust.hk/~jshuaa/papers/mmsys18_cardea.pdf" target="_blank">https://web.archive.org/web/20181108184408/https://home.cse.ust.hk/~jshuaa/papers/mmsys18_cardea.pdf</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li>
<li id="fn:6"><p>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. <a href="9781467369640" target="_blank">9781467369640</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li>
<li id="fn:7"><p>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. <a href="#fnref:7" class="footnote-back-ref">↩</a></p></li>
<li id="fn:8"><p>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. <a href="9781450355681" target="_blank">9781450355681</a> <a href="#fnref:8" class="footnote-back-ref">↩</a></p></li>
</ol>

Visual privacy open-in-new

Visual privacy