Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems

Object recognition and localisation are important processes in computer vision and robotics. Advances in computer vision have resulted in many object recognition techniques, but most of them are computationally very intensive and require robots with powerful processing systems. For small robots, the...

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Detalhes bibliográficos
Autores: Ahmed, M. Shuja, Saatchi, Reza, Caparrelli, Fabio
Tipo de documento: artigo
Data de publicação:2012
País:España
Recursos:Universitat Autònoma de Barcelona
Repositório:Dipòsit Digital de Documents de la UAB
Idioma:inglês
OAI Identifier:oai:ddd.uab.cat:102552
Acesso em linha:https://ddd.uab.cat/record/102552
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.486
Access Level:Acceso aberto
Palavra-chave:Object Recognition
Localisation
Multi-camera tracking
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spelling Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic SystemsAhmed, M. ShujaSaatchi, RezaCaparrelli, FabioObject RecognitionLocalisationMulti-camera trackingObject recognition and localisation are important processes in computer vision and robotics. Advances in computer vision have resulted in many object recognition techniques, but most of them are computationally very intensive and require robots with powerful processing systems. For small robots, these techniques are not applicable because of the constraints of execution time. In this study, an optimised implementation of SURF based recognition technique is presented. Suitable image pre-processing techniques were developed which reduced the recognition time on small robots with limited processing resources. The recognition time was reduced from 39 seconds to 780 milliseconds. This recognition technique was adopted by a team of small robots which were given prior training to search for objects of interest in the environment. For the localisation of the robots and objects a new template, designed for passive markers based tracking, was introduced. These markers were placed on the top of each robot and they were tracked by the two ceiling mounted cameras. The information from both sources, that is ceiling mounted cameras and team of robots, was used collectively to localise the objects in the environment. The objects were localised with an error ranging from 2.8cm to 5.2cm from their actual positions in the test arena which has the dimensions of 150x163cm. 22012-01-0120122012-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/102552https://dx.doi.org/urn:doi:10.5565/rev/elcvia.486reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.https://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:1025522026-06-06T12:50:31Z
dc.title.none.fl_str_mv Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
title Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
spellingShingle Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
Ahmed, M. Shuja
Object Recognition
Localisation
Multi-camera tracking
title_short Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
title_full Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
title_fullStr Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
title_full_unstemmed Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
title_sort Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
dc.creator.none.fl_str_mv Ahmed, M. Shuja
Saatchi, Reza
Caparrelli, Fabio
author Ahmed, M. Shuja
author_facet Ahmed, M. Shuja
Saatchi, Reza
Caparrelli, Fabio
author_role author
author2 Saatchi, Reza
Caparrelli, Fabio
author2_role author
author
dc.subject.none.fl_str_mv Object Recognition
Localisation
Multi-camera tracking
topic Object Recognition
Localisation
Multi-camera tracking
description Object recognition and localisation are important processes in computer vision and robotics. Advances in computer vision have resulted in many object recognition techniques, but most of them are computationally very intensive and require robots with powerful processing systems. For small robots, these techniques are not applicable because of the constraints of execution time. In this study, an optimised implementation of SURF based recognition technique is presented. Suitable image pre-processing techniques were developed which reduced the recognition time on small robots with limited processing resources. The recognition time was reduced from 39 seconds to 780 milliseconds. This recognition technique was adopted by a team of small robots which were given prior training to search for objects of interest in the environment. For the localisation of the robots and objects a new template, designed for passive markers based tracking, was introduced. These markers were placed on the top of each robot and they were tracked by the two ceiling mounted cameras. The information from both sources, that is ceiling mounted cameras and team of robots, was used collectively to localise the objects in the environment. The objects were localised with an error ranging from 2.8cm to 5.2cm from their actual positions in the test arena which has the dimensions of 150x163cm.
publishDate 2012
dc.date.none.fl_str_mv 2
2012-01-01
2012
2012-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
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 https://ddd.uab.cat/record/102552
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.486
url https://ddd.uab.cat/record/102552
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.486
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
https://creativecommons.org/licenses/by-nc-nd/3.0/
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
https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
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