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dc.contributor.authorNurena-Jara, Roberto
dc.contributor.authorRamos-Carrion, Cristopher
dc.contributor.authorShiguihara-Juarez, Pedro
dc.date.accessioned2021-07-06T17:43:28Z
dc.date.available2021-07-06T17:43:28Z
dc.date.issued2020-10-21
dc.identifier.doi10.1109/EIRCON51178.2020.9254019
dc.identifier.urihttp://hdl.handle.net/10757/656634
dc.descriptionEl texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.en_US
dc.description.abstractPeruvian Sign Language Recognition (PSL) is approached as a classification problem. Previous work has employed 2D features from the position of hands to tackle this problem. In this paper, we propose a method to construct a dataset consisting of 3D spatial positions of static gestures from the PSL alphabet, using the HTC Vive device and a well-known technique to extract 21 keypoints from the hand to obtain a feature vector. A dataset of 35, 400 instances of gestures for PSL was constructed and a novel way to extract data was stated. To validate the appropriateness of this dataset, a comparison of four baselines classifiers in the Peruvian Sign Language Recognition (PSLR) task was stated, achieving 99.32% in the average in terms of F1 measure in the best case.en_US
dc.formatapplication/htmlen_US
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.urlhttps://ieeexplore.ieee.org/document/9254019en_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectgesture recognitionen_US
dc.subjectPeruvian sign languageen_US
dc.subjectsign language recognitionen_US
dc.titleData collection of 3D spatial features of gestures from static peruvian sign language alphabet for sign language recognitionen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.journalProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020en_US
dc.description.peerreviewRevisión por pareses_PE
dc.identifier.eid2-s2.0-85097807930
dc.identifier.scopusidSCOPUS_ID:85097807930
dc.source.journaltitleProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020


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