Artificial intelligence to estimate wine volume from single-view images
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COBO CANO, MIRIAM; Heredia Cacha, Ignacio; Aguilar Gómez, Fernando; Lloret Iglesias, Lara; GARCIA DIAZ, DANIEL; Bartolomé, Begoña; Moreno-Arribas, Victoria M.; Yuste, Silvia; Pérez-Matute, Patricia; Motilva, Maria-JoseFecha
2022Derechos
Attribution-NonCommercial-NoDerivatives 4.0 International
Publicado en
Heliyon, 2022, 8, e10557
Editorial
Elsevier
Enlace a la publicación
Palabras clave
Deep learning model
Quantitative red wine volume estimation
Single-view image
Resumen/Abstract
In this paper, we present a method to determine the volume of wine in different types of glass liquid containers
from a single-view image. The proposed model predicts red wine volume from a photograph of the glass
containing the wine. Experimental results demonstrated satisfactory performance of our image-based wine
measurement system, with a Mean Absolute Error lower than 10 mL. To train and evaluate our system, we
introduced the WineGut_BrainUp dataset, a new dataset of glasses of wine that contains 24305 laboratory images, including a wide range of containers, volumes of wine, backgrounds, object distances, angles and lightning, with or without calibration object. The proposed methodology is a suitable analytical tool for automate measurement of red wine volume. Indeed, it has potential real life applications in diet monitoring and wine consumption studies.
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