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HGM-4: A new multi-cameras dataset for hand gesture recognition

Gesture recognition technology is rapidly growing in the recent years due to the demands of many application such as computer game and sport, human robot interaction, assistant systems, sign language interpretation and e-commerce. One of the most important of gesture recognition is hand-gesture reco...

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Detalles Bibliográficos
Autor principal: Hoang, V.T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229479/
https://www.ncbi.nlm.nih.gov/pubmed/32435681
http://dx.doi.org/10.1016/j.dib.2020.105676
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author Hoang, V.T.
author_facet Hoang, V.T.
author_sort Hoang, V.T.
collection PubMed
description Gesture recognition technology is rapidly growing in the recent years due to the demands of many application such as computer game and sport, human robot interaction, assistant systems, sign language interpretation and e-commerce. One of the most important of gesture recognition is hand-gesture recognition. For example, it can be used to control all devices (television, radio, air-condition, and doors) by just hand gestures for smart home application. The HGM-4 dataset is built for hand gesture recognition (the full dataset is available from: https://data.mendeley.com/datasets/jzy8zngkbg/4) which contains total 4,160 color images (1280 × 700 pixels) of 26 hand gestures captured by four cameras at different position. The training and testing set are defined to create a benchmark framework for comparing the experimental results.
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spelling pubmed-72294792020-05-20 HGM-4: A new multi-cameras dataset for hand gesture recognition Hoang, V.T. Data Brief Computer Science Gesture recognition technology is rapidly growing in the recent years due to the demands of many application such as computer game and sport, human robot interaction, assistant systems, sign language interpretation and e-commerce. One of the most important of gesture recognition is hand-gesture recognition. For example, it can be used to control all devices (television, radio, air-condition, and doors) by just hand gestures for smart home application. The HGM-4 dataset is built for hand gesture recognition (the full dataset is available from: https://data.mendeley.com/datasets/jzy8zngkbg/4) which contains total 4,160 color images (1280 × 700 pixels) of 26 hand gestures captured by four cameras at different position. The training and testing set are defined to create a benchmark framework for comparing the experimental results. Elsevier 2020-05-08 /pmc/articles/PMC7229479/ /pubmed/32435681 http://dx.doi.org/10.1016/j.dib.2020.105676 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Hoang, V.T.
HGM-4: A new multi-cameras dataset for hand gesture recognition
title HGM-4: A new multi-cameras dataset for hand gesture recognition
title_full HGM-4: A new multi-cameras dataset for hand gesture recognition
title_fullStr HGM-4: A new multi-cameras dataset for hand gesture recognition
title_full_unstemmed HGM-4: A new multi-cameras dataset for hand gesture recognition
title_short HGM-4: A new multi-cameras dataset for hand gesture recognition
title_sort hgm-4: a new multi-cameras dataset for hand gesture recognition
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229479/
https://www.ncbi.nlm.nih.gov/pubmed/32435681
http://dx.doi.org/10.1016/j.dib.2020.105676
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