Main areas detection on tennis courts

ABSTRACT : This paper is going to show all the ETL process, which includes obtaining of the images, label process of images of tennis matches with the objective of detecting the main areas of the court. The process continues with the generation of a baseline using a heuristic process and the generat...

Full description

Autores:
Arroyave Lopez, Juliana
Echavarria Echeverri, Rodrigo Alejandro
Tipo de recurso:
Tesis
Fecha de publicación:
2021
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/24642
Acceso en línea:
http://hdl.handle.net/10495/24642
Palabra clave:
Inteligencia artificial
Visión por computador
Computer vision
Artificial intelligence
Procesamiento de imagen
Image processing
Aprendizaje automático (inteligencia artificial)
Semantic segmentatio
Object detection
Multiclass classification
Hough transform
U-Net
Deep-learning
Python
Segmentación semántica
Detección de objetos
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-sa/2.5/co/
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oai_identifier_str oai:bibliotecadigital.udea.edu.co:10495/24642
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network_name_str Repositorio UdeA
repository_id_str
dc.title.spa.fl_str_mv Main areas detection on tennis courts
dc.title.alternative.spa.fl_str_mv Detección de areas significativas en canchas de tenis
title Main areas detection on tennis courts
spellingShingle Main areas detection on tennis courts
Inteligencia artificial
Visión por computador
Computer vision
Artificial intelligence
Procesamiento de imagen
Image processing
Aprendizaje automático (inteligencia artificial)
Semantic segmentatio
Object detection
Multiclass classification
Hough transform
U-Net
Deep-learning
Python
Segmentación semántica
Detección de objetos
title_short Main areas detection on tennis courts
title_full Main areas detection on tennis courts
title_fullStr Main areas detection on tennis courts
title_full_unstemmed Main areas detection on tennis courts
title_sort Main areas detection on tennis courts
dc.creator.fl_str_mv Arroyave Lopez, Juliana
Echavarria Echeverri, Rodrigo Alejandro
dc.contributor.advisor.none.fl_str_mv Sepulveda Cano, Lina Maria
dc.contributor.author.none.fl_str_mv Arroyave Lopez, Juliana
Echavarria Echeverri, Rodrigo Alejandro
dc.subject.lemb.none.fl_str_mv Inteligencia artificial
Visión por computador
Computer vision
Artificial intelligence
Procesamiento de imagen
Image processing
Aprendizaje automático (inteligencia artificial)
topic Inteligencia artificial
Visión por computador
Computer vision
Artificial intelligence
Procesamiento de imagen
Image processing
Aprendizaje automático (inteligencia artificial)
Semantic segmentatio
Object detection
Multiclass classification
Hough transform
U-Net
Deep-learning
Python
Segmentación semántica
Detección de objetos
dc.subject.proposal.spa.fl_str_mv Semantic segmentatio
Object detection
Multiclass classification
Hough transform
U-Net
Deep-learning
Python
Segmentación semántica
Detección de objetos
description ABSTRACT : This paper is going to show all the ETL process, which includes obtaining of the images, label process of images of tennis matches with the objective of detecting the main areas of the court. The process continues with the generation of a baseline using a heuristic process and the generation of a deep learning model, with modification on the characteristics of the images, that allows the detection of main areas on the tennis courts, as well as the pick of the best option for the task selected, based on their performance.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-12-07T18:45:31Z
dc.date.available.none.fl_str_mv 2021-12-07T18:45:31Z
dc.date.issued.none.fl_str_mv 2021
dc.type.spa.fl_str_mv info:eu-repo/semantics/other
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.hasversion.spa.fl_str_mv info:eu-repo/semantics/draft
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_46ec
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/COther
dc.type.local.spa.fl_str_mv Tesis/Trabajo de grado - Monografía - Especialización
format http://purl.org/coar/resource_type/c_46ec
status_str draft
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10495/24642
url http://hdl.handle.net/10495/24642
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/co/
dc.rights.accessrights.spa.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.creativecommons.spa.fl_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/co/
http://purl.org/coar/access_right/c_abf2
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dc.format.extent.spa.fl_str_mv 8
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.place.spa.fl_str_mv Medellín
institution Universidad de Antioquia
bitstream.url.fl_str_mv http://bibliotecadigital.udea.edu.co/bitstream/10495/24642/6/license.txt
http://bibliotecadigital.udea.edu.co/bitstream/10495/24642/1/ArroyaveJuliana_2021TennisCourtDetection.pdf
http://bibliotecadigital.udea.edu.co/bitstream/10495/24642/5/license_rdf
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repository.name.fl_str_mv Repositorio Institucional Universidad de Antioquia
repository.mail.fl_str_mv andres.perez@udea.edu.co
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spelling Sepulveda Cano, Lina MariaArroyave Lopez, JulianaEchavarria Echeverri, Rodrigo Alejandro2021-12-07T18:45:31Z2021-12-07T18:45:31Z2021http://hdl.handle.net/10495/24642ABSTRACT : This paper is going to show all the ETL process, which includes obtaining of the images, label process of images of tennis matches with the objective of detecting the main areas of the court. The process continues with the generation of a baseline using a heuristic process and the generation of a deep learning model, with modification on the characteristics of the images, that allows the detection of main areas on the tennis courts, as well as the pick of the best option for the task selected, based on their performance.8application/pdfenginfo:eu-repo/semantics/draftinfo:eu-repo/semantics/otherhttp://purl.org/coar/resource_type/c_46echttp://purl.org/redcol/resource_type/COtherTesis/Trabajo de grado - Monografía - Especializaciónhttp://purl.org/coar/version/c_b1a7d7d4d402bcceinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/co/http://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by-nc-sa/4.0/Main areas detection on tennis courtsDetección de areas significativas en canchas de tenisMedellínInteligencia artificialVisión por computadorComputer visionArtificial intelligenceProcesamiento de imagenImage processingAprendizaje automático (inteligencia artificial)Semantic segmentatioObject detectionMulticlass classificationHough transformU-NetDeep-learningPythonSegmentación semánticaDetección de objetoshttps://github.com/rechavar/pyTennishttps://github.com/rechavar/py_tennis_mlcouldEspecialista en Analítica y Ciencia de DatosEspecializaciónFacultad de Ingeniería. Especialización en Analítica y Ciencia de DatosUniversidad de AntioquiaLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://bibliotecadigital.udea.edu.co/bitstream/10495/24642/6/license.txt8a4605be74aa9ea9d79846c1fba20a33MD56ORIGINALArroyaveJuliana_2021TennisCourtDetection.pdfArroyaveJuliana_2021TennisCourtDetection.pdfTrabajo de grado de especializaciónapplication/pdf6418217http://bibliotecadigital.udea.edu.co/bitstream/10495/24642/1/ArroyaveJuliana_2021TennisCourtDetection.pdf76edaa97344a7604f3a809b89fcd3b29MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81051http://bibliotecadigital.udea.edu.co/bitstream/10495/24642/5/license_rdfe2060682c9c70d4d30c83c51448f4eedMD5510495/24642oai:bibliotecadigital.udea.edu.co:10495/246422021-12-07 13:49:58.475Repositorio Institucional Universidad de Antioquiaandres.perez@udea.edu.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