Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.

Human-Robot interaction represents a cornerstone of mobile robotics, especially within the field of social robots. In this context, user localization becomes of crucial importance for the interaction. This work investigates the capabilities of wide field-of-view RGB cameras to estimate the 3D positi...

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Detalles Bibliográficos
Autores: Garcia-Salguero, Mercedes, Gonzalez-Jimenez, Javier, Moreno, Francisco-Angel
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Instituto de Salud Carlos III (ISCIII)
Repositorio:Repisalud
Idioma:inglés
OAI Identifier:oai:repisalud.isciii.es:20.500.12105/17932
Acceso en línea:http://hdl.handle.net/20.500.12105/17932
Access Level:acceso abierto
Palabra clave:3D computer vision
OpenPose
RGB-D cameras
Camera pose calibration
Human body pose estimation
Human–robot interaction
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spelling Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.Garcia-Salguero, MercedesGonzalez-Jimenez, JavierMoreno, Francisco-Angel3D computer visionOpenPoseRGB-D camerasCamera pose calibrationHuman body pose estimationHuman–robot interactionHuman-Robot interaction represents a cornerstone of mobile robotics, especially within the field of social robots. In this context, user localization becomes of crucial importance for the interaction. This work investigates the capabilities of wide field-of-view RGB cameras to estimate the 3D position and orientation (i.e., the pose) of a user in the environment. For that, we employ a social robot endowed with a fish-eye camera hosted in a tilting head and develop two complementary approaches: (1) a fast method relying on a single image that estimates the user pose from the detection of their feet and does not require either the robot or the user to remain static during the reconstruction; and (2) a method that takes some views of the scene while the camera is being tilted and does not need the feet to be visible. Due to the particular setup of the tilting camera, special equations for 3D reconstruction have been developed. In both approaches, a CNN-based skeleton detector (OpenPose) is employed to identify humans within the image. A set of experiments with real data validate our two proposed methods, yielding similar results than commercial RGB-D cameras while surpassing them in terms of coverage of the scene (wider FoV and longer range) and robustness to light conditions.20242024-02-1020192019-11-1320192019-11-13research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articlehttp://hdl.handle.net/20.500.12105/17932reponame:Repisaludinstname:Instituto de Salud Carlos III (ISCIII)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repisalud.isciii.es:20.500.12105/179322026-06-12T12:43:37Z
dc.title.none.fl_str_mv Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
title Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
spellingShingle Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
Garcia-Salguero, Mercedes
3D computer vision
OpenPose
RGB-D cameras
Camera pose calibration
Human body pose estimation
Human–robot interaction
title_short Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
title_full Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
title_fullStr Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
title_full_unstemmed Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
title_sort Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.
dc.creator.none.fl_str_mv Garcia-Salguero, Mercedes
Gonzalez-Jimenez, Javier
Moreno, Francisco-Angel
author Garcia-Salguero, Mercedes
author_facet Garcia-Salguero, Mercedes
Gonzalez-Jimenez, Javier
Moreno, Francisco-Angel
author_role author
author2 Gonzalez-Jimenez, Javier
Moreno, Francisco-Angel
author2_role author
author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv 3D computer vision
OpenPose
RGB-D cameras
Camera pose calibration
Human body pose estimation
Human–robot interaction
topic 3D computer vision
OpenPose
RGB-D cameras
Camera pose calibration
Human body pose estimation
Human–robot interaction
description Human-Robot interaction represents a cornerstone of mobile robotics, especially within the field of social robots. In this context, user localization becomes of crucial importance for the interaction. This work investigates the capabilities of wide field-of-view RGB cameras to estimate the 3D position and orientation (i.e., the pose) of a user in the environment. For that, we employ a social robot endowed with a fish-eye camera hosted in a tilting head and develop two complementary approaches: (1) a fast method relying on a single image that estimates the user pose from the detection of their feet and does not require either the robot or the user to remain static during the reconstruction; and (2) a method that takes some views of the scene while the camera is being tilted and does not need the feet to be visible. Due to the particular setup of the tilting camera, special equations for 3D reconstruction have been developed. In both approaches, a CNN-based skeleton detector (OpenPose) is employed to identify humans within the image. A set of experiments with real data validate our two proposed methods, yielding similar results than commercial RGB-D cameras while surpassing them in terms of coverage of the scene (wider FoV and longer range) and robustness to light conditions.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-11-13
2019
2019-11-13
2024
2024-02-10
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12105/17932
url http://hdl.handle.net/20.500.12105/17932
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repisalud
instname:Instituto de Salud Carlos III (ISCIII)
instname_str Instituto de Salud Carlos III (ISCIII)
reponame_str Repisalud
collection Repisalud
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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