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dc.contributor.advisorCostin, Andrei
dc.contributor.authorLahtinen, Tuomo
dc.date.accessioned2022-04-25T10:05:14Z
dc.date.available2022-04-25T10:05:14Z
dc.date.issued2022
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/80691
dc.description.abstractCamera surveillance has become a worldwide phenomenon that affects the lives of almost every person. People are not aware of how much they are entering the surveillance zone and for some people the patronizing surveillance may raise concerns about individual freedom and privacy. This paper introduces a browser extension that allows users to annotate cameras to build a security / privacy type of navigation that avoids or follows cameras. Image annotation started with describing images with words that have evolved to annotate images in more detail, and today large datasets can be used for ML/CV model training. The purpose of the browser extension was to annotate images in a way that training of ML/CV models to recognize CCTV cameras from Google Street View images is possible. The browser extension was tested with the crowdsourcing effort where eight different people used the extension in different browsers and different operating systems, after which the people evaluated the extensions functionality and ease of use. The evaluation showed that the extension works as indented and it is an effective tool for annotating images. In addition, the extension succeeded in training ML/CV models to recognize CCTV cameras from Street View-level images.en
dc.format.extent84
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subject.otherbrowser extension
dc.subject.otherAPI
dc.titleNovel browser extension tool for image annotation : (Applications and use-cases in a novel CCTV-aware system)
dc.identifier.urnURN:NBN:fi:jyu-202204252368
dc.type.ontasotPro gradu -tutkielmafi
dc.type.ontasotMaster’s thesisen
dc.contributor.tiedekuntaInformaatioteknologian tiedekuntafi
dc.contributor.tiedekuntaFaculty of Information Technologyen
dc.contributor.laitosInformaatioteknologiafi
dc.contributor.laitosInformation Technologyen
dc.contributor.yliopistoJyväskylän yliopistofi
dc.contributor.yliopistoUniversity of Jyväskyläen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.rights.copyrightJulkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.fi
dc.rights.copyrightThis publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.en
dc.type.publicationmasterThesis
dc.contributor.oppiainekoodi602
dc.subject.ysotekoäly
dc.subject.ysotietosuoja
dc.subject.ysoyksityisyys
dc.subject.ysokameravalvonta
dc.subject.ysoohjelmointi
dc.subject.ysokoneoppiminen
dc.subject.ysoannotointi
dc.subject.ysoJavaScript
dc.subject.ysoartificial intelligence
dc.subject.ysodata protection
dc.subject.ysoprivacy
dc.subject.ysoclosed-circuit television
dc.subject.ysoprogramming
dc.subject.ysomachine learning
dc.subject.ysoannotation
dc.subject.ysoJavaScript
dc.format.contentfulltext
dc.rights.accessrightsTekijä ei ole antanut lupaa avoimeen julkaisuun, joten aineisto on luettavissa vain Jyväskylän yliopiston kirjaston arkistotyösemalta. Ks. https://kirjasto.jyu.fi/kokoelmat/arkistotyoasema..fi
dc.rights.accessrightsThe author has not given permission to make the work publicly available electronically. Therefore the material can be read only at the archival workstation at Jyväskylä University Library (https://kirjasto.jyu.fi/collections/archival-workstation).en
dc.type.okmG2


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