Accurate abandoned object detection (AOD) in surveillance video
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações do ITA |
Texto Completo: | http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3230 |
Resumo: | The aim of the present research is to investigate the problem known as Abandoned Object Detection (AOD) in surveillance videos, where stationary objects must be classified as either abandoned or removed. We found four categories of methods to solve the AOD problem, namely, region growing, edge detection, color comparison and image inpainting and investigated all of them. We found the major drawback of each category, from which we derived guidelines that oriented the development of three novel methods. Among these three methods, the proposed method (based on edge detection) measures the ratio of a blob boundary that is covered by edges in the reference image. This method achieved convincing results on 66 test scenarios compared to results of most recent works in the literature, equaling or surpassing these results. Furthermore, we proposed a frame window scheme to combine the information from several frames about a given object in order to provide a robust classification. The experiments show our method achieved and surpassed the state-of-the-art results. |
id |
ITA_8da1deb12bc20f9557c50d63e463ad55 |
---|---|
oai_identifier_str |
oai:agregador.ibict.br.BDTD_ITA:oai:ita.br:3230 |
network_acronym_str |
ITA |
network_name_str |
Biblioteca Digital de Teses e Dissertações do ITA |
spelling |
Accurate abandoned object detection (AOD) in surveillance videoSinais de vídeoRastreamento (posição)Indicadores de alvos móveisVigilânciaProcessamento de sinaisTelecomunicaçõesComputaçãoEngenharia eletrônicaThe aim of the present research is to investigate the problem known as Abandoned Object Detection (AOD) in surveillance videos, where stationary objects must be classified as either abandoned or removed. We found four categories of methods to solve the AOD problem, namely, region growing, edge detection, color comparison and image inpainting and investigated all of them. We found the major drawback of each category, from which we derived guidelines that oriented the development of three novel methods. Among these three methods, the proposed method (based on edge detection) measures the ratio of a blob boundary that is covered by edges in the reference image. This method achieved convincing results on 66 test scenarios compared to results of most recent works in the literature, equaling or surpassing these results. Furthermore, we proposed a frame window scheme to combine the information from several frames about a given object in order to provide a robust classification. The experiments show our method achieved and surpassed the state-of-the-art results.Instituto Tecnológico de AeronáuticaOsamu SaotomeDaniel Julien Barros da Silva SampaioAlex Lopes Pereira2015-04-13info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesishttp://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3230reponame:Biblioteca Digital de Teses e Dissertações do ITAinstname:Instituto Tecnológico de Aeronáuticainstacron:ITAenginfo:eu-repo/semantics/openAccessapplication/pdf2019-02-02T14:05:08Zoai:agregador.ibict.br.BDTD_ITA:oai:ita.br:3230http://oai.bdtd.ibict.br/requestopendoar:null2020-05-28 19:41:25.014Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáuticatrue |
dc.title.none.fl_str_mv |
Accurate abandoned object detection (AOD) in surveillance video |
title |
Accurate abandoned object detection (AOD) in surveillance video |
spellingShingle |
Accurate abandoned object detection (AOD) in surveillance video Alex Lopes Pereira Sinais de vídeo Rastreamento (posição) Indicadores de alvos móveis Vigilância Processamento de sinais Telecomunicações Computação Engenharia eletrônica |
title_short |
Accurate abandoned object detection (AOD) in surveillance video |
title_full |
Accurate abandoned object detection (AOD) in surveillance video |
title_fullStr |
Accurate abandoned object detection (AOD) in surveillance video |
title_full_unstemmed |
Accurate abandoned object detection (AOD) in surveillance video |
title_sort |
Accurate abandoned object detection (AOD) in surveillance video |
author |
Alex Lopes Pereira |
author_facet |
Alex Lopes Pereira |
author_role |
author |
dc.contributor.none.fl_str_mv |
Osamu Saotome Daniel Julien Barros da Silva Sampaio |
dc.contributor.author.fl_str_mv |
Alex Lopes Pereira |
dc.subject.por.fl_str_mv |
Sinais de vídeo Rastreamento (posição) Indicadores de alvos móveis Vigilância Processamento de sinais Telecomunicações Computação Engenharia eletrônica |
topic |
Sinais de vídeo Rastreamento (posição) Indicadores de alvos móveis Vigilância Processamento de sinais Telecomunicações Computação Engenharia eletrônica |
dc.description.none.fl_txt_mv |
The aim of the present research is to investigate the problem known as Abandoned Object Detection (AOD) in surveillance videos, where stationary objects must be classified as either abandoned or removed. We found four categories of methods to solve the AOD problem, namely, region growing, edge detection, color comparison and image inpainting and investigated all of them. We found the major drawback of each category, from which we derived guidelines that oriented the development of three novel methods. Among these three methods, the proposed method (based on edge detection) measures the ratio of a blob boundary that is covered by edges in the reference image. This method achieved convincing results on 66 test scenarios compared to results of most recent works in the literature, equaling or surpassing these results. Furthermore, we proposed a frame window scheme to combine the information from several frames about a given object in order to provide a robust classification. The experiments show our method achieved and surpassed the state-of-the-art results. |
description |
The aim of the present research is to investigate the problem known as Abandoned Object Detection (AOD) in surveillance videos, where stationary objects must be classified as either abandoned or removed. We found four categories of methods to solve the AOD problem, namely, region growing, edge detection, color comparison and image inpainting and investigated all of them. We found the major drawback of each category, from which we derived guidelines that oriented the development of three novel methods. Among these three methods, the proposed method (based on edge detection) measures the ratio of a blob boundary that is covered by edges in the reference image. This method achieved convincing results on 66 test scenarios compared to results of most recent works in the literature, equaling or surpassing these results. Furthermore, we proposed a frame window scheme to combine the information from several frames about a given object in order to provide a robust classification. The experiments show our method achieved and surpassed the state-of-the-art results. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-04-13 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
status_str |
publishedVersion |
format |
doctoralThesis |
dc.identifier.uri.fl_str_mv |
http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3230 |
url |
http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3230 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Instituto Tecnológico de Aeronáutica |
publisher.none.fl_str_mv |
Instituto Tecnológico de Aeronáutica |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações do ITA instname:Instituto Tecnológico de Aeronáutica instacron:ITA |
reponame_str |
Biblioteca Digital de Teses e Dissertações do ITA |
collection |
Biblioteca Digital de Teses e Dissertações do ITA |
instname_str |
Instituto Tecnológico de Aeronáutica |
instacron_str |
ITA |
institution |
ITA |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáutica |
repository.mail.fl_str_mv |
|
subject_por_txtF_mv |
Sinais de vídeo Rastreamento (posição) Indicadores de alvos móveis Vigilância Processamento de sinais Telecomunicações Computação Engenharia eletrônica |
_version_ |
1706809297383456768 |