PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/s11042-019-07958-7 http://hdl.handle.net/11449/194955 |
Resumo: | Extracting elements of interest from video frames is a necessary task in many applications, such as those that require replacing the original background. Quality assessment of foreground extraction algorithms is essential to find the best algorithm for a particular application. This paper presents an application-dependent objective metric capable of evaluating the quality of those algorithms by considering user perception. Our metric identifies types of errors that cause the greatest annoyance based on regions of the scene where users tend to keep their attention during videoconference sessions. We demonstrate the efficiency of our metric by evaluating bilayer segmentation algorithms. The results showed that metric is effective compared to others used to evaluate algorithms for videoconferencing systems. |
id |
UNSP_01694fe49d9de4e47464cc367cbecd5b |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/194955 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithmsObjective metricSegmentation qualitySegmentation evaluationVideoconferenceExtracting elements of interest from video frames is a necessary task in many applications, such as those that require replacing the original background. Quality assessment of foreground extraction algorithms is essential to find the best algorithm for a particular application. This paper presents an application-dependent objective metric capable of evaluating the quality of those algorithms by considering user perception. Our metric identifies types of errors that cause the greatest annoyance based on regions of the scene where users tend to keep their attention during videoconference sessions. We demonstrate the efficiency of our metric by evaluating bilayer segmentation algorithms. The results showed that metric is effective compared to others used to evaluate algorithms for videoconferencing systems.Univ Tecnol Fed Parana, Cornelio Procopio, PR, BrazilUniv Estadual Paulista, Bauru, BrazilUniv Sao Paulo, Escola Politecn, Sao Paulo, BrazilUniv Sao Paulo, Sao Paulo, BrazilUniv Estadual Paulista, Bauru, BrazilSpringerUniv Tecnol Fed ParanaUniversidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)Sanches, Silvio R. R.Sementille, Antonio C. [UNESP]Tori, RomeroNakamura, RicardoFreire, Valdinei2020-12-10T16:59:51Z2020-12-10T16:59:51Z2019-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article32393-32417http://dx.doi.org/10.1007/s11042-019-07958-7Multimedia Tools And Applications. Dordrecht: Springer, v. 78, n. 22, p. 32393-32417, 2019.1380-7501http://hdl.handle.net/11449/19495510.1007/s11042-019-07958-7WOS:000495400000059Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMultimedia Tools And Applicationsinfo:eu-repo/semantics/openAccess2021-10-23T03:03:18Zoai:repositorio.unesp.br:11449/194955Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:27:09.439790Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms |
title |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms |
spellingShingle |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms Sanches, Silvio R. R. Objective metric Segmentation quality Segmentation evaluation Videoconference |
title_short |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms |
title_full |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms |
title_fullStr |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms |
title_full_unstemmed |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms |
title_sort |
PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms |
author |
Sanches, Silvio R. R. |
author_facet |
Sanches, Silvio R. R. Sementille, Antonio C. [UNESP] Tori, Romero Nakamura, Ricardo Freire, Valdinei |
author_role |
author |
author2 |
Sementille, Antonio C. [UNESP] Tori, Romero Nakamura, Ricardo Freire, Valdinei |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Univ Tecnol Fed Parana Universidade Estadual Paulista (Unesp) Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Sanches, Silvio R. R. Sementille, Antonio C. [UNESP] Tori, Romero Nakamura, Ricardo Freire, Valdinei |
dc.subject.por.fl_str_mv |
Objective metric Segmentation quality Segmentation evaluation Videoconference |
topic |
Objective metric Segmentation quality Segmentation evaluation Videoconference |
description |
Extracting elements of interest from video frames is a necessary task in many applications, such as those that require replacing the original background. Quality assessment of foreground extraction algorithms is essential to find the best algorithm for a particular application. This paper presents an application-dependent objective metric capable of evaluating the quality of those algorithms by considering user perception. Our metric identifies types of errors that cause the greatest annoyance based on regions of the scene where users tend to keep their attention during videoconference sessions. We demonstrate the efficiency of our metric by evaluating bilayer segmentation algorithms. The results showed that metric is effective compared to others used to evaluate algorithms for videoconferencing systems. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-11-01 2020-12-10T16:59:51Z 2020-12-10T16:59:51Z |
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 |
http://dx.doi.org/10.1007/s11042-019-07958-7 Multimedia Tools And Applications. Dordrecht: Springer, v. 78, n. 22, p. 32393-32417, 2019. 1380-7501 http://hdl.handle.net/11449/194955 10.1007/s11042-019-07958-7 WOS:000495400000059 |
url |
http://dx.doi.org/10.1007/s11042-019-07958-7 http://hdl.handle.net/11449/194955 |
identifier_str_mv |
Multimedia Tools And Applications. Dordrecht: Springer, v. 78, n. 22, p. 32393-32417, 2019. 1380-7501 10.1007/s11042-019-07958-7 WOS:000495400000059 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Multimedia Tools And Applications |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
32393-32417 |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129203844939776 |