Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras

© 2018 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to...

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Detalles Bibliográficos
Autores: López Cifuentes, Alejandro, Escudero Viñolo, Marcos, Bescos Cano, Jesús
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/692467
Acceso en línea:http://hdl.handle.net/10486/692467
https://dx.doi.org/10.1109/LSP.2018.2865833
Access Level:acceso abierto
Palabra clave:Multiple moving cameras
Semantic segmentation
Area of interest
PTZ
Video surveillance
Scene parsing
Telecomunicaciones
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spelling Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving camerasLópez Cifuentes, AlejandroEscudero Viñolo, MarcosBescos Cano, JesúsMultiple moving camerasSemantic segmentationArea of interestPTZVideo surveillanceScene parsingTelecomunicaciones© 2018 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Nowadays, video surveillance scenarios usually rely on manually annotated focus areas to constrain automatic video analysis tasks. Whereas manual annotation simplifies several stages of the analysis, its use hinders the scalability of the developed solutions and might induce operational problems in scenarios recorded with Multiple and Moving Cameras (MMC). To tackle these problems, an automatic method for the cooperative extraction of Areas of Interest (AoIs) is proposed. Each captured frame is segmented into regions with semantic roles using a stateof- the-art method. Semantic evidences from different junctures, cameras and points-of-view are then spatio-temporally aligned on a common ground plane. Experimental results on widely-used datasets recorded with multiple but static cameras suggest that this process provides broader and more accurate AoIs than those manually defined in the datasets. Moreover, the proposed method naturally determines the projection of obstacles and functional objects in the scene, paving the road towards systems focused on the automatic analysis of human behaviour. To our knowledge, this is the first study dealing with this problematic, as evidenced by the lack of publicly available MMC benchmarks. To also cope with this issue, we provide a new MMC dataset with associated semantic scene annotationsThis study has been partially supported by the Spanish Government through its TEC2014-53176-R HAVideo projectInstitute of Electrical and Electronics EngineersDepartamento de Tecnología Electrónica y de las ComunicacionesEscuela Politécnica SuperiorTratamiento e Interpretación de Vídeo (ING EPS-006)20182018-08-17research articlehttp://purl.org/coar/resource_type/c_2df8fbb1AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/692467https://dx.doi.org/10.1109/LSP.2018.2865833reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/6924672026-06-23T12:46:27Z
dc.title.none.fl_str_mv Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
title Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
spellingShingle Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
López Cifuentes, Alejandro
Multiple moving cameras
Semantic segmentation
Area of interest
PTZ
Video surveillance
Scene parsing
Telecomunicaciones
title_short Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
title_full Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
title_fullStr Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
title_full_unstemmed Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
title_sort Automatic semantic parsing of the ground-plane in scenarios recorded with multiple moving cameras
dc.creator.none.fl_str_mv López Cifuentes, Alejandro
Escudero Viñolo, Marcos
Bescos Cano, Jesús
author López Cifuentes, Alejandro
author_facet López Cifuentes, Alejandro
Escudero Viñolo, Marcos
Bescos Cano, Jesús
author_role author
author2 Escudero Viñolo, Marcos
Bescos Cano, Jesús
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Tecnología Electrónica y de las Comunicaciones
Escuela Politécnica Superior
Tratamiento e Interpretación de Vídeo (ING EPS-006)
dc.subject.none.fl_str_mv Multiple moving cameras
Semantic segmentation
Area of interest
PTZ
Video surveillance
Scene parsing
Telecomunicaciones
topic Multiple moving cameras
Semantic segmentation
Area of interest
PTZ
Video surveillance
Scene parsing
Telecomunicaciones
description © 2018 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-08-17
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10486/692467
https://dx.doi.org/10.1109/LSP.2018.2865833
url http://hdl.handle.net/10486/692467
https://dx.doi.org/10.1109/LSP.2018.2865833
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
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
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:Biblos-e Archivo. Repositorio Institucional de la UAM
instname:Universidad Autónoma de Madrid
instname_str Universidad Autónoma de Madrid
reponame_str Biblos-e Archivo. Repositorio Institucional de la UAM
collection Biblos-e Archivo. Repositorio Institucional de la UAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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