dc.contributor.author | Turtiainen, Hannu | |
dc.contributor.author | Costin, Andrei | |
dc.contributor.author | Hämäläinen, Timo | |
dc.contributor.author | Lahtinen, Tuomo | |
dc.contributor.author | Sintonen, Lauri | |
dc.date.accessioned | 2023-03-22T10:30:28Z | |
dc.date.available | 2023-03-22T10:30:28Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Turtiainen, H., Costin, A., Hämäläinen, T., Lahtinen, T., & Sintonen, L. (2022). CCTV-FullyAware : toward end-to-end feasible privacy-enhancing and CCTV forensics applications. In <i>TrustCom 2022 : Proceedings of the IEEE 21st International Conference on Trust, Security and Privacy in Computing and Communications </i> (pp. 1227-1234). IEEE. IEEE International Conference on Trust, Security and Privacy in Computing and Communications. <a href="https://doi.org/10.1109/trustcom56396.2022.00170" target="_blank">https://doi.org/10.1109/trustcom56396.2022.00170</a> | |
dc.identifier.other | CONVID_176940802 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/86092 | |
dc.description.abstract | It is estimated that over 1 billion Closed-Circuit Television (CCTV) cameras are operational worldwide. The advertised main benefits of CCTV cameras have always been the same; physical security, safety, and crime deterrence. The current scale and rate of deployment of CCTV cameras bring additional research and technical challenges for CCTV forensics as well, as for privacy enhancements. This paper presents the first end-to-end system for CCTV forensics and feasible privacy-enhancing applications such as exposure measurement, CCTV route recovery, CCTV-aware routing/navigation, and crowd-sourcing. For this, we developed and evaluated four complex and distinct modules (CCTVCV [1], OSRM-CCTV [2], BRIMA [3], CCTV-Exposure [4]), all of which are novel, unique, peer-reviewed, and can be used either separately or within an integrated end-to-end system such as CCTV-FullyAware. We release all our artefacts as open-source/open data. We hope our work will bootstrap policy-driving discussions and large-scale applications such as CCTV forensics and privacy-enhancing technologies. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | IEEE | |
dc.relation.ispartof | TrustCom 2022 : Proceedings of the IEEE 21st International Conference on Trust, Security and Privacy in Computing and Communications | |
dc.relation.ispartofseries | IEEE International Conference on Trust, Security and Privacy in Computing and Communications | |
dc.rights | In Copyright | |
dc.subject.other | machine learning | |
dc.subject.other | navigation | |
dc.subject.other | object detection | |
dc.subject.other | privacy-enhancing technologies | |
dc.subject.other | video surveillance | |
dc.title | CCTV-FullyAware : toward end-to-end feasible privacy-enhancing and CCTV forensics applications | |
dc.type | conferenceObject | |
dc.identifier.urn | URN:NBN:fi:jyu-202303222241 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.relation.isbn | 978-1-6654-9426-7 | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 1227-1234 | |
dc.relation.issn | 2324-898X | |
dc.type.version | acceptedVersion | |
dc.rights.copyright | © 2022 IEEE | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.conference | IEEE International Conference On Trust, Security And Privacy In Computing And Communications | |
dc.subject.yso | tekninen rikostutkinta | |
dc.subject.yso | yksilönsuoja | |
dc.subject.yso | koneoppiminen | |
dc.subject.yso | sovellusohjelmat | |
dc.subject.yso | yksityisyys | |
dc.subject.yso | konenäkö | |
dc.subject.yso | kameravalvonta | |
dc.subject.yso | tietosuoja | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p28613 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p3637 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p21846 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p8456 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p10909 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2618 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p4713 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p3636 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.1109/trustcom56396.2022.00170 | |
jyx.fundinginformation | The authors acknowledge the grants of computer capacity from the Finnish Grid and Cloud Infrastructure (persistent identifier urn:nbn:fi:research-infras-2016072533). Part of this research was supported by a grant from the Decision of the Research Dean on research funding within the Faculty (07.04.2021), and Decision of the Research Dean on research funding within the Faculty (20.04.2022) of the Faculty of Information Technology of University of Jyväskylä. Hannu Turtiainen also thanks the Finnish Cultural Foundation / Suomen Kulttuurirahasto (https://skr.fi/en) for supporting his Ph.D. dissertation work and research (under grant decision no.00221059) and the Faculty of Information Technology of the University of Jyväskylä (JYU), in particular, Prof. Timo Hämäläinen, for partly supporting and supervising his Ph.D. work at JYU in 2021–2023. The authors also acknowledge the use of royalty-free icons courtesy of www.flaticon.com (icons by: Good Ware, Freepik, itim2101, Pixel perfect, Icongeek26, Eucalyp, prettycons, and Stockio). Map image in Fig. 4 is generated with Folium (for Python) library (https://python-visualization.github.io/folium/) using OpenStreetMap data (https://www.openstreetmap.org). | |
dc.type.okm | A4 | |