Título:	Automatic grape bunch detection in vineyards based on affordable 3D phenotyping using a consumer webcam.
Autor:	SANTOS, T. T. BASSOI, L. H. OLDONI, H. MARTINS, R. L.
Afiliación:	THIAGO TEIXEIRA SANTOS, CNPTIA; LUIS HENRIQUE BASSOI, CNPDIA; HENRIQUE OLDONI, Unesp Botucatu; ROBERTO LUVISUTTO MARTINS, Unesp Botucatu.
Año:	2017
Referencia:	In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 11., 2017, Campinas. Ciência de dados na era da agricultura digital: anais. Campinas: Editora da Unicamp: Embrapa Informática Agropecuária, 2017.
Páginas:	p. 89-98.
Descripción:	This work presents a methodology for 3-D phenotyping of vineyards based on images captured by a low cost high-definition webcamera. A novel software application integrated visual odometry and multiple-view stereo components to create dense and accurate three-dimensional points clouds for vines, properly transformed to millimeter scale. Geometrical and color features of the points were employed by a classification procedure that reached 93% of accuracy on detecting points belonging to grapes. Individual bunches were automatically delimited and their volumes estimated. The sum of the estimated volumes per vine presented a coefficient of correlation of R = 0.99 to the real grape weight observed in each vine after harvesting.
Thesagro:	Viticultura
NAL Thesaurus:	Viticulture Phenotype
Palabras clave:	Estimativa de podução Métodos não-invasivos Fenotipagem 3D Visão estéro múltipla Simultaneous localization and mapping Yield estimation Non-invasive methods 3-D phenotyping Multiple view stereo Videira
ISBN:	978-85-85783-75-4
Notas:	SBIAgro 2017.
Tipo de Material:	Artigo em anais e proceedings
Acceso:	openAccess
Aparece en las colecciones:	Artigo em anais de congresso (CNPTIA)