@article{10902/31857,
year = {2022},
url = {https://hdl.handle.net/10902/31857},
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.},
publisher = {Elsevier},
publisher = {Heliyon, 2022, 8, e10557},
title = {Artificial intelligence to estimate wine volume from single-view images},
author = {Cobo Cano, Miriam and Heredia Cacha, Ignacio and Aguilar Gómez, Fernando and Lloret Iglesias, Lara and García Díaz, Daniel and Bartolomé, Begoña and Moreno-Arribas, Victoria M. and Yuste, Silvia and Pérez-Matute, Patricia and Motilva, Maria-Jose},
}