Human gait identification using persistent homology

This paper shows an image/video application using topological invariants for human gait recognition. Using a background subtraction approach, a stack of silhouettes is extracted from a subsequence and glued through their gravity centers, forming a 3D digital image I. From this 3D representation, the...

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Detalles Bibliográficos
Autores: Lamar León, Javier, García Reyes, Edel, González Díaz, Rocío
Tipo de recurso: capítulo de libro
Fecha de publicación:2012
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/30814
Acceso en línea:http://hdl.handle.net/11441/30814
https://doi.org/10.1007/978-3-642-33275-3_30
Access Level:acceso abierto
Palabra clave:Pattern Recognition
Image Processing and Computer Vision
Artificial Intelligence (incl. Robotics)
Biometrics
Algorithm Analysis and Problem Complexity
Information Systems Applications (incl. Internet)
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spelling Human gait identification using persistent homologyLamar León, JavierGarcía Reyes, EdelGonzález Díaz, RocíoPattern RecognitionImage Processing and Computer VisionArtificial Intelligence (incl. Robotics)BiometricsAlgorithm Analysis and Problem ComplexityInformation Systems Applications (incl. Internet)This paper shows an image/video application using topological invariants for human gait recognition. Using a background subtraction approach, a stack of silhouettes is extracted from a subsequence and glued through their gravity centers, forming a 3D digital image I. From this 3D representation, the border simplicial complex ∂ K(I) is obtained. We order the triangles of ∂ K(I) obtaining a sequence of subcomplexes of ∂ K(I). The corresponding filtration F captures relations among the parts of the human body when walking. Finally, a topological gait signature is extracted from the persistence barcode according to F. In this work we obtain 98.5% correct classification rates on CASIA-B database.Matemática Aplicada I2012info:eu-repo/semantics/bookPartapplication/pdfapplication/pdfhttp://hdl.handle.net/11441/30814https://doi.org/10.1007/978-3-642-33275-3_30reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, Lecture Notes in Computer Science, Vol. 7441 p. 244-251info:eu-repo/semantics/openAccessoai:idus.us.es:11441/308142026-06-17T12:51:07Z
dc.title.none.fl_str_mv Human gait identification using persistent homology
title Human gait identification using persistent homology
spellingShingle Human gait identification using persistent homology
Lamar León, Javier
Pattern Recognition
Image Processing and Computer Vision
Artificial Intelligence (incl. Robotics)
Biometrics
Algorithm Analysis and Problem Complexity
Information Systems Applications (incl. Internet)
title_short Human gait identification using persistent homology
title_full Human gait identification using persistent homology
title_fullStr Human gait identification using persistent homology
title_full_unstemmed Human gait identification using persistent homology
title_sort Human gait identification using persistent homology
dc.creator.none.fl_str_mv Lamar León, Javier
García Reyes, Edel
González Díaz, Rocío
author Lamar León, Javier
author_facet Lamar León, Javier
García Reyes, Edel
González Díaz, Rocío
author_role author
author2 García Reyes, Edel
González Díaz, Rocío
author2_role author
author
dc.contributor.none.fl_str_mv Matemática Aplicada I
dc.subject.none.fl_str_mv Pattern Recognition
Image Processing and Computer Vision
Artificial Intelligence (incl. Robotics)
Biometrics
Algorithm Analysis and Problem Complexity
Information Systems Applications (incl. Internet)
topic Pattern Recognition
Image Processing and Computer Vision
Artificial Intelligence (incl. Robotics)
Biometrics
Algorithm Analysis and Problem Complexity
Information Systems Applications (incl. Internet)
description This paper shows an image/video application using topological invariants for human gait recognition. Using a background subtraction approach, a stack of silhouettes is extracted from a subsequence and glued through their gravity centers, forming a 3D digital image I. From this 3D representation, the border simplicial complex ∂ K(I) is obtained. We order the triangles of ∂ K(I) obtaining a sequence of subcomplexes of ∂ K(I). The corresponding filtration F captures relations among the parts of the human body when walking. Finally, a topological gait signature is extracted from the persistence barcode according to F. In this work we obtain 98.5% correct classification rates on CASIA-B database.
publishDate 2012
dc.date.none.fl_str_mv 2012
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv http://hdl.handle.net/11441/30814
https://doi.org/10.1007/978-3-642-33275-3_30
url http://hdl.handle.net/11441/30814
https://doi.org/10.1007/978-3-642-33275-3_30
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, Lecture Notes in Computer Science, Vol. 7441 p. 244-251
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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