Demo: FaceBlock: privacy-aware pictures for google glass

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dc.contributor.authorYus, Roberto
dc.contributor.authorPappachan, Primal
dc.contributor.authorDas, Prajit Kumar
dc.contributor.authorMena, Eduardo
dc.contributor.authorJoshi, Anupam
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-02T14:10:59Z
dc.date.available2018-11-02T14:10:59Z
dc.date.issued2014-06-16
dc.descriptionProceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Servicesen_US
dc.description.abstractFaceBlock takes regular pictures taken by your smartphone or Google Glass as input and converts them into Privacy-Aware Pictures. These pictures are generated by using a combination of Face Detection and Face Recognition algorithms. By using FaceBlock, a user can take a picture of herself and specify her policy/rule regarding pictures taken by others (in this case ‘obscure my face in pictures from strangers’). FaceBlock would automatically generate a mathematical representation of face identifier for this picture. Using Bluetooth, FaceBlock can automatically detect and share this policy with Glass users near by. FaceBlock is a proof of concept implementation of a system that can create Privacy-Aware Pictures using smart devices. The pervasiveness of Privacy-Aware Pictures could be a right step towards balancing privacy needs and comfort afforded by technology. Thus, we can get the best out of Wearable technology without being oblivious about the privacy of those around you.en_US
dc.description.sponsorshipWork supported by CICYT TIN2010-21387-C02-02, DGA -FSE, NSF 0910838 and MURI FA9550-08-1-0265.en_US
dc.description.urihttps://dl.acm.org/citation.cfm?id=2601473en_US
dc.format.extent1 pageen_US
dc.genreconference papers and proceedings and slidesen_US
dc.identifierdoi:10.13016/M20K26G01
dc.identifier.citationRoberto Yus, Primal Pappachan, Prajit Kumar Das, Eduardo Mena, Anupam Joshi, and Tim Finin, Demo: FaceBlock: privacy-aware pictures for google glass, Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, pages 366-366, Doi :10.1145/2594368.2601473en_US
dc.identifier.uri10.1145/2594368.2601473
dc.identifier.urihttp://hdl.handle.net/11603/11836
dc.language.isoen_USen_US
dc.publisherACM SIGMOBILEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectGoogle Glassen_US
dc.subjectprivacy-aware picturesen_US
dc.subjectpolicy sharingen_US
dc.subjectFaceBlocken_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleDemo: FaceBlock: privacy-aware pictures for google glassen_US
dc.title.alternativeFaceBlock: Privacy-Aware Pictures for Google Glassen_US
dc.typeTexten_US

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