Hand Detection In Static Images, Video Sequences And Real Time Camera Feed

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but.event.date25.04.2019cs
but.event.titleStudent EEICT 2019cs
dc.contributor.authorBravenec, Tomáš
dc.date.accessioned2020-04-16T07:19:35Z
dc.date.available2020-04-16T07:19:35Z
dc.date.issued2019cs
dc.description.abstractThe goal of this project is to create a computer vision system capable of hand detection in static images and in video sequence either from existing recording or real time feed from connected camera. Algorithms commonly used for hand detection are mostly dependent on simple background and are very dependent on the lightning changes. To mostly eliminate these issues this project uses deep convolutional neural network trained for hand detection.en
dc.formattextcs
dc.format.extent386-389cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 25st Conference STUDENT EEICT 2019. s. 386-389. ISBN 978-80-214-5735-5cs
dc.identifier.isbn978-80-214-5735-5
dc.identifier.urihttp://hdl.handle.net/11012/186699
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 25st Conference STUDENT EEICT 2019en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectComputer Visionen
dc.subjectHand detectionen
dc.subjectConvolutional Neural Networksen
dc.subjectDeep Learningen
dc.titleHand Detection In Static Images, Video Sequences And Real Time Camera Feeden
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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