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Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Agrossilvipastoril. |
Data corrente: |
04/01/2022 |
Data da última atualização: |
06/01/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
SANTOS, E. F. dos; VENDRUSCULO, L. G.; LOPES, L. B.; KAMCHEN, S. G.; CONDOTTA, I. C. F. S. |
Afiliação: |
ELTON FERNANDES DOS SANTOS, UFMT; LAURIMAR GONCALVES VENDRUSCULO, CNPTIA; LUCIANO BASTOS LOPES, CPAMT; SCHEILA GEIELE KAMCHEN, UFMT; ISABELLA C. F. S. CONDOTTA, University of Illinois. |
Título: |
Mathematical models for metric features extraction from RGB-D sensor. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Scientific Electronic Archives, v. 14, n. 11, p. 76-85, 2021. |
DOI: |
https://doi.org/10.36560/141120211467 |
Idioma: |
Inglês |
Conteúdo: |
Abstract. The use of the RGB-D camera has been applied in several fields of science. That popularization is due to the emergence of technologies such as the Intel® RealSenseTM D400 series. However, despite the actual demand from some potential users, few studies concern the characterization of these sensors for object measurements. Our study sought to estimate models dealing with calculating the area and length between targets or points within RGB and depth images. An experiment was set up with white cardboard fixed on a flat surface with colored pins. We measured the distance between the camera and cardboard by calculating the average distance from the pixels belonging to the target area. The Information Criterion AIC and BIC associated with R2 were performed to select the best models. Polynomial and power regression models reached the highest coefficient of determination and smallest values of AIC and BIC. |
Palavras-Chave: |
Depth camera; Extração de características; Image processing; Modelos matemáticos; Processamento de imagem; RealSenseTM. |
Thesaurus Nal: |
Image analysis; Mathematical models. |
Categoria do assunto: |
-- X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/229943/1/AP-Mathematical-models-2021.pdf
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Marc: |
LEADER 01776naa a2200277 a 4500 001 2138727 005 2022-01-06 008 2021 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.36560/141120211467$2DOI 100 1 $aSANTOS, E. F. dos 245 $aMathematical models for metric features extraction from RGB-D sensor.$h[electronic resource] 260 $c2021 520 $aAbstract. The use of the RGB-D camera has been applied in several fields of science. That popularization is due to the emergence of technologies such as the Intel® RealSenseTM D400 series. However, despite the actual demand from some potential users, few studies concern the characterization of these sensors for object measurements. Our study sought to estimate models dealing with calculating the area and length between targets or points within RGB and depth images. An experiment was set up with white cardboard fixed on a flat surface with colored pins. We measured the distance between the camera and cardboard by calculating the average distance from the pixels belonging to the target area. The Information Criterion AIC and BIC associated with R2 were performed to select the best models. Polynomial and power regression models reached the highest coefficient of determination and smallest values of AIC and BIC. 650 $aImage analysis 650 $aMathematical models 653 $aDepth camera 653 $aExtração de características 653 $aImage processing 653 $aModelos matemáticos 653 $aProcessamento de imagem 653 $aRealSenseTM 700 1 $aVENDRUSCULO, L. G. 700 1 $aLOPES, L. B. 700 1 $aKAMCHEN, S. G. 700 1 $aCONDOTTA, I. C. F. S. 773 $tScientific Electronic Archives$gv. 14, n. 11, p. 76-85, 2021.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sul. Para informações adicionais entre em contato com cppsul.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Pecuária Sul. |
Data corrente: |
24/09/2015 |
Data da última atualização: |
07/03/2016 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
YOKOO, M. J. I.; LÔBO, R. B.; MAGNABOSCO, C. de U.; ROSA, G. J. M.; FORNI, S.; SAINZ, R. D.; ALBUQUERQUE, L. G. |
Afiliação: |
MARCOS JUN ITI YOKOO, CPPSUL; R. B. Lôbo, Associação Nacional de Criadores e Pesquisadores; CLAUDIO DE ULHOA MAGNABOSCO, CPAC; G. J. M. Rosa, University of Wisconsin; S. Forni, Dow AgroSciences; R. D. Sainz, University of California; L. G. Albuquerque, UNESP. |
Título: |
Genetic correlation of traits measured by ultrasound at yearling and 18 months of age in Nellore beef cattle. |
Ano de publicação: |
2015 |
Fonte/Imprenta: |
Livestock Science, v. 180, p. 34-40, Oct. 2015. |
DOI: |
10.1016/j.livsci.2015.07.003 |
Idioma: |
Inglês |
Conteúdo: |
The objective of this study was to estimate genetic parameters for carcass traits measured by ultrasound at yearling (Y) and 18 months of age (post-yearling, PY) in order to identify the most appropriate age for the measurement of these traits used for the selection of Nellore beef cattle. |
Palavras-Chave: |
Ultra-Som. |
Thesagro: |
Carcaça; Gado de corte. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01013naa a2200241 a 4500 001 2024924 005 2016-03-07 008 2015 bl uuuu u00u1 u #d 024 7 $a10.1016/j.livsci.2015.07.003$2DOI 100 1 $aYOKOO, M. J. I. 245 $aGenetic correlation of traits measured by ultrasound at yearling and 18 months of age in Nellore beef cattle.$h[electronic resource] 260 $c2015 520 $aThe objective of this study was to estimate genetic parameters for carcass traits measured by ultrasound at yearling (Y) and 18 months of age (post-yearling, PY) in order to identify the most appropriate age for the measurement of these traits used for the selection of Nellore beef cattle. 650 $aCarcaça 650 $aGado de corte 653 $aUltra-Som 700 1 $aLÔBO, R. B. 700 1 $aMAGNABOSCO, C. de U. 700 1 $aROSA, G. J. M. 700 1 $aFORNI, S. 700 1 $aSAINZ, R. D. 700 1 $aALBUQUERQUE, L. G. 773 $tLivestock Science$gv. 180, p. 34-40, Oct. 2015.
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