Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction

Bibliographic Details
Main Author: Mendes, Nuno
Publication Date: 2017
Other Authors: Ferrer, João, Vitorino, João, Safeea, Mohammad, Neto, Pedro
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/10316/102073
https://doi.org/10.1016/j.promfg.2017.07.156
Summary: This paper presents an intuitive human-robot interaction (HRI) framework for gesture and human behavior recognition. It relies on a vision-based system as interaction technology to classify gestures and a 3-axis accelerometer for behavior classification (stand, walking, etc.). An intelligent system integrates static gesture recognition recurring to artificial neural networks (ANNs) and dynamic gesture recognition using hidden Markov models (HMM). Results show a recognition rate of 95% for a library of 22 gestures and 97% for a library of 6 behaviors. Experiments show a robot controlled using gestures in a HRI process.
id RCAP_fbbbf64b53be3b49423c5a28e1631e8a
oai_identifier_str oai:estudogeral.uc.pt:10316/102073
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Human Behavior and Hand Gesture Classification for Smart Human-robot InteractionHuman Robot InteractionHuman Behavior RecognitionGesturesSegmentationAccelerometerThis paper presents an intuitive human-robot interaction (HRI) framework for gesture and human behavior recognition. It relies on a vision-based system as interaction technology to classify gestures and a 3-axis accelerometer for behavior classification (stand, walking, etc.). An intelligent system integrates static gesture recognition recurring to artificial neural networks (ANNs) and dynamic gesture recognition using hidden Markov models (HMM). Results show a recognition rate of 95% for a library of 22 gestures and 97% for a library of 6 behaviors. Experiments show a robot controlled using gestures in a HRI process.2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/102073https://hdl.handle.net/10316/102073https://doi.org/10.1016/j.promfg.2017.07.156eng23519789Mendes, NunoFerrer, JoãoVitorino, JoãoSafeea, MohammadNeto, Pedroinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-12-11T12:12:31Zoai:estudogeral.uc.pt:10316/102073Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:51:23.450085Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
title Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
spellingShingle Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
Mendes, Nuno
Human Robot Interaction
Human Behavior Recognition
Gestures
Segmentation
Accelerometer
title_short Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
title_full Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
title_fullStr Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
title_full_unstemmed Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
title_sort Human Behavior and Hand Gesture Classification for Smart Human-robot Interaction
author Mendes, Nuno
author_facet Mendes, Nuno
Ferrer, João
Vitorino, João
Safeea, Mohammad
Neto, Pedro
author_role author
author2 Ferrer, João
Vitorino, João
Safeea, Mohammad
Neto, Pedro
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Mendes, Nuno
Ferrer, João
Vitorino, João
Safeea, Mohammad
Neto, Pedro
dc.subject.por.fl_str_mv Human Robot Interaction
Human Behavior Recognition
Gestures
Segmentation
Accelerometer
topic Human Robot Interaction
Human Behavior Recognition
Gestures
Segmentation
Accelerometer
description This paper presents an intuitive human-robot interaction (HRI) framework for gesture and human behavior recognition. It relies on a vision-based system as interaction technology to classify gestures and a 3-axis accelerometer for behavior classification (stand, walking, etc.). An intelligent system integrates static gesture recognition recurring to artificial neural networks (ANNs) and dynamic gesture recognition using hidden Markov models (HMM). Results show a recognition rate of 95% for a library of 22 gestures and 97% for a library of 6 behaviors. Experiments show a robot controlled using gestures in a HRI process.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10316/102073
https://hdl.handle.net/10316/102073
https://doi.org/10.1016/j.promfg.2017.07.156
url https://hdl.handle.net/10316/102073
https://doi.org/10.1016/j.promfg.2017.07.156
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 23519789
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833602496368476160

Similar Items