Small face detection using deep learning on surveillance videos

dc.contributor.affiliationPontificia Universidad Católica del Perú
dc.contributor.authorCárdenas, R.J.
dc.contributor.authorBeltrán Castañón, C.A.
dc.contributor.authorGutiérrez, J.C.
dc.date.accessioned2026-03-13T16:58:18Z
dc.date.issued2019
dc.description.abstractFace detection is one of the essential tasks widely studied in the field of Computer Vision. Several authors have developed different techniques to improve the face detection in images, but these are limited in their application on videos and more if they present low resolution. In this study, we propose a new model for face detection in low-resolution videos based on the morphology of the upper body of people, and the use of Deep Learning (CNN). Our results show an average of 39% accuracy over the Caviar dataset and 32% in the UCSP dataset. Compared with other techniques, our results are greater due they only reach 1% of accuracy.
dc.description.sponsorshipFunding: This research was supported by CIENCIACTIVA, CONCYTEC, and the National University of San Agustin (UNSA). The authors thank all the professors who collaborated in this research.
dc.identifier.doihttps://doi.org/10.18178/ijmlc.2019.9.2.785
dc.identifier.urihttp://hdl.handle.net/20.500.14657/205833
dc.language.isoeng
dc.publisherInternational Association of Computer Science and Information Technology
dc.relation.ispartofurn:issn:2010-3700
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.sourceInternational Journal of Machine Learning and Computing; Vol. 9, Núm. 2 (2019)
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectFace (sociological concept)
dc.subjectFace detection
dc.subjectDeep learning
dc.subjectMachine learning
dc.subjectComputer vision
dc.subjectFacial recognition system
dc.subjectPattern recognition (psychology)
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.01
dc.titleSmall face detection using deep learning on surveillance videos
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.type.otherArtículo
dc.type.versionhttps://vocabularies.coar-repositories.org/version_types/c_970fb48d4fbd8a85/

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