Phenological visual rhythms: Compact representations for fine-grained plant species identification
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.patrec.2015.11.028 http://hdl.handle.net/11449/177732 |
Resumo: | Plant phenology, the study of recurrent life cycles events and its relationship to climate, is a key discipline in climate change research. In this context, digital cameras have been effectively used to monitor leaf flushing and senescence on vegetations across the world. A primary condition for the phenological observation refers to the correct identification of plants by taking into account time series associated with their crowns in the digital images. In this paper, we present a novel approach for representing phenological patterns of plant species. The proposed method is based on encoding time series as a visual rhythm. Here, we focus on applications of our approach for plant species identification. In this scenario, visual rhythms are characterized by image description algorithms. A comparative analysis of different descriptors is conducted and discussed. Experimental results show that our approach presents high accuracy on identifying individual plant species from its specific visual rhythm. Additionally, our representation is compact, making it suitable for long-term data series. |
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Repositório Institucional da UNESP |
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2946 |
spelling |
Phenological visual rhythms: Compact representations for fine-grained plant species identificationImage analysisPlant identificationRemote phenologyTime seriesVisual rhythmPlant phenology, the study of recurrent life cycles events and its relationship to climate, is a key discipline in climate change research. In this context, digital cameras have been effectively used to monitor leaf flushing and senescence on vegetations across the world. A primary condition for the phenological observation refers to the correct identification of plants by taking into account time series associated with their crowns in the digital images. In this paper, we present a novel approach for representing phenological patterns of plant species. The proposed method is based on encoding time series as a visual rhythm. Here, we focus on applications of our approach for plant species identification. In this scenario, visual rhythms are characterized by image description algorithms. A comparative analysis of different descriptors is conducted and discussed. Experimental results show that our approach presents high accuracy on identifying individual plant species from its specific visual rhythm. Additionally, our representation is compact, making it suitable for long-term data series.Institute of Science and Technology Federal University of São Paulo – UNIFESPDepartment of Computer Science Federal University of Minas Gerais – UFMGDept. of Botany São Paulo State University – UNESPInstitute of Computing University of Campinas – UNICAMPDept. of Botany São Paulo State University – UNESPUniversidade de São Paulo (USP)Universidade Federal de Minas Gerais (UFMG)Universidade Estadual Paulista (Unesp)Universidade Estadual de Campinas (UNICAMP)Almeida, Jurandydos Santos, Jefersson A.Alberton, Bruna [UNESP]Morellato, Leonor Patricia C. [UNESP]da S. Torres, Ricardo2018-12-11T17:26:49Z2018-12-11T17:26:49Z2016-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article90-100application/pdfhttp://dx.doi.org/10.1016/j.patrec.2015.11.028Pattern Recognition Letters, v. 81, p. 90-100.0167-8655http://hdl.handle.net/11449/17773210.1016/j.patrec.2015.11.0282-s2.0-849552714392-s2.0-84955271439.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPattern Recognition Letters0,662info:eu-repo/semantics/openAccess2023-11-07T06:14:15Zoai:repositorio.unesp.br:11449/177732Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:06:28.354946Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Phenological visual rhythms: Compact representations for fine-grained plant species identification |
title |
Phenological visual rhythms: Compact representations for fine-grained plant species identification |
spellingShingle |
Phenological visual rhythms: Compact representations for fine-grained plant species identification Almeida, Jurandy Image analysis Plant identification Remote phenology Time series Visual rhythm |
title_short |
Phenological visual rhythms: Compact representations for fine-grained plant species identification |
title_full |
Phenological visual rhythms: Compact representations for fine-grained plant species identification |
title_fullStr |
Phenological visual rhythms: Compact representations for fine-grained plant species identification |
title_full_unstemmed |
Phenological visual rhythms: Compact representations for fine-grained plant species identification |
title_sort |
Phenological visual rhythms: Compact representations for fine-grained plant species identification |
author |
Almeida, Jurandy |
author_facet |
Almeida, Jurandy dos Santos, Jefersson A. Alberton, Bruna [UNESP] Morellato, Leonor Patricia C. [UNESP] da S. Torres, Ricardo |
author_role |
author |
author2 |
dos Santos, Jefersson A. Alberton, Bruna [UNESP] Morellato, Leonor Patricia C. [UNESP] da S. Torres, Ricardo |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Federal de Minas Gerais (UFMG) Universidade Estadual Paulista (Unesp) Universidade Estadual de Campinas (UNICAMP) |
dc.contributor.author.fl_str_mv |
Almeida, Jurandy dos Santos, Jefersson A. Alberton, Bruna [UNESP] Morellato, Leonor Patricia C. [UNESP] da S. Torres, Ricardo |
dc.subject.por.fl_str_mv |
Image analysis Plant identification Remote phenology Time series Visual rhythm |
topic |
Image analysis Plant identification Remote phenology Time series Visual rhythm |
description |
Plant phenology, the study of recurrent life cycles events and its relationship to climate, is a key discipline in climate change research. In this context, digital cameras have been effectively used to monitor leaf flushing and senescence on vegetations across the world. A primary condition for the phenological observation refers to the correct identification of plants by taking into account time series associated with their crowns in the digital images. In this paper, we present a novel approach for representing phenological patterns of plant species. The proposed method is based on encoding time series as a visual rhythm. Here, we focus on applications of our approach for plant species identification. In this scenario, visual rhythms are characterized by image description algorithms. A comparative analysis of different descriptors is conducted and discussed. Experimental results show that our approach presents high accuracy on identifying individual plant species from its specific visual rhythm. Additionally, our representation is compact, making it suitable for long-term data series. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-10-01 2018-12-11T17:26:49Z 2018-12-11T17:26:49Z |
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/10.1016/j.patrec.2015.11.028 Pattern Recognition Letters, v. 81, p. 90-100. 0167-8655 http://hdl.handle.net/11449/177732 10.1016/j.patrec.2015.11.028 2-s2.0-84955271439 2-s2.0-84955271439.pdf |
url |
http://dx.doi.org/10.1016/j.patrec.2015.11.028 http://hdl.handle.net/11449/177732 |
identifier_str_mv |
Pattern Recognition Letters, v. 81, p. 90-100. 0167-8655 10.1016/j.patrec.2015.11.028 2-s2.0-84955271439 2-s2.0-84955271439.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Pattern Recognition Letters 0,662 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
90-100 application/pdf |
dc.source.none.fl_str_mv |
Scopus 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_ |
1808128756408123392 |