A robot-based surveillance system for recognising distress hand signal

[EN] Unfortunately, there are still cases of domestic violence or situations where it is necessary to call for help without arousing the suspicion of the aggressor. In these situations, the help signal devised by the Canadian Women's Foundation has proven to be effective in reporting a risky si...

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Detalles Bibliográficos
Autores: Riego Del Castillo, Virginia, Sánchez González, Lidia, González Santamarta, Miguel Ángel, Rodríguez Lera, Francisco Javier
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2024
País:España
Institución:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/20546
Acceso en línea:https://hdl.handle.net/10612/20546
Access Level:acceso abierto
Palabra clave:Ingenierías
Computer Vision
Social Robots
Distress Hand Signal
Cognitive Architecture
3304.05 Sistemas de Reconocimiento de Caracteres
6114.18 Comunicación Simbólica
id ES_e89fe5c5e3ca6e732cc4e77ce678ebb2
oai_identifier_str oai:buleria.unileon.es:10612/20546
network_acronym_str ES
network_name_str España
repository_id_str
spelling A robot-based surveillance system for recognising distress hand signalRiego Del Castillo, VirginiaSánchez González, LidiaGonzález Santamarta, Miguel ÁngelRodríguez Lera, Francisco JavierIngenieríasComputer VisionSocial RobotsDistress Hand SignalCognitive Architecture3304.05 Sistemas de Reconocimiento de Caracteres6114.18 Comunicación Simbólica[EN] Unfortunately, there are still cases of domestic violence or situations where it is necessary to call for help without arousing the suspicion of the aggressor. In these situations, the help signal devised by the Canadian Women's Foundation has proven to be effective in reporting a risky situation. By displaying a sequence of hand signals, it is possible to report that help is needed. This work presents a vision-based system that detects this sequence and implements it in a social robot, so that it can automatically identify unwanted situations and alert the authorities. The gesture recognition pipeline presented in this work is integrated into a cognitive architecture used to generate behaviours in robots. In this way, the robot interacts with humans and is able to detect if a person is calling for help. In that case, the robot will act accordingly without alerting the aggressor. The proposed vision system uses the MediaPipe library to detect people in an image and locate the hands, from which it extracts a set of hand landmarks that identify which gesture is being made. By analysing the sequence of detected gestures, it can identify whether a person is performing the distress hand signal with an accuracy of 96.43%.SIAgencia Estatal de InvestigaciónEDMAR Project PID2021-126592OB-C21 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making EuropeOxford University PressArquitectura y Tecnologia de ComputadoresEscuela de Ingenierias Industrial, Informática y Aeroespacial2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttps://hdl.handle.net/10612/20546reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad de LeónInglésinfo:eu-repo/grantAgreement/ AEI / Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia/PID2021-126592OB-C21info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/205462026-06-24T12:43:27Z
dc.title.none.fl_str_mv A robot-based surveillance system for recognising distress hand signal
title A robot-based surveillance system for recognising distress hand signal
spellingShingle A robot-based surveillance system for recognising distress hand signal
Riego Del Castillo, Virginia
Ingenierías
Computer Vision
Social Robots
Distress Hand Signal
Cognitive Architecture
3304.05 Sistemas de Reconocimiento de Caracteres
6114.18 Comunicación Simbólica
title_short A robot-based surveillance system for recognising distress hand signal
title_full A robot-based surveillance system for recognising distress hand signal
title_fullStr A robot-based surveillance system for recognising distress hand signal
title_full_unstemmed A robot-based surveillance system for recognising distress hand signal
title_sort A robot-based surveillance system for recognising distress hand signal
dc.creator.none.fl_str_mv Riego Del Castillo, Virginia
Sánchez González, Lidia
González Santamarta, Miguel Ángel
Rodríguez Lera, Francisco Javier
author Riego Del Castillo, Virginia
author_facet Riego Del Castillo, Virginia
Sánchez González, Lidia
González Santamarta, Miguel Ángel
Rodríguez Lera, Francisco Javier
author_role author
author2 Sánchez González, Lidia
González Santamarta, Miguel Ángel
Rodríguez Lera, Francisco Javier
author2_role author
author
author
dc.contributor.none.fl_str_mv Arquitectura y Tecnologia de Computadores
Escuela de Ingenierias Industrial, Informática y Aeroespacial
dc.subject.none.fl_str_mv Ingenierías
Computer Vision
Social Robots
Distress Hand Signal
Cognitive Architecture
3304.05 Sistemas de Reconocimiento de Caracteres
6114.18 Comunicación Simbólica
topic Ingenierías
Computer Vision
Social Robots
Distress Hand Signal
Cognitive Architecture
3304.05 Sistemas de Reconocimiento de Caracteres
6114.18 Comunicación Simbólica
description [EN] Unfortunately, there are still cases of domestic violence or situations where it is necessary to call for help without arousing the suspicion of the aggressor. In these situations, the help signal devised by the Canadian Women's Foundation has proven to be effective in reporting a risky situation. By displaying a sequence of hand signals, it is possible to report that help is needed. This work presents a vision-based system that detects this sequence and implements it in a social robot, so that it can automatically identify unwanted situations and alert the authorities. The gesture recognition pipeline presented in this work is integrated into a cognitive architecture used to generate behaviours in robots. In this way, the robot interacts with humans and is able to detect if a person is calling for help. In that case, the robot will act accordingly without alerting the aggressor. The proposed vision system uses the MediaPipe library to detect people in an image and locate the hands, from which it extracts a set of hand landmarks that identify which gesture is being made. By analysing the sequence of detected gestures, it can identify whether a person is performing the distress hand signal with an accuracy of 96.43%.
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/10612/20546
url https://hdl.handle.net/10612/20546
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/ AEI / Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia/PID2021-126592OB-C21
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:BULERIA. Repositorio Institucional de la Universidad de León
instname:Universidad de León
instname_str Universidad de León
reponame_str BULERIA. Repositorio Institucional de la Universidad de León
collection BULERIA. Repositorio Institucional de la Universidad de León
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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