Cargando…
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...
Autor principal: | |
---|---|
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 |
_version_ | 1783534771991740416 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7229479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT hoangvt hgm4anewmulticamerasdatasetforhandgesturerecognition |