This is the list of publications of this laboratory
2019
Journal Articles
Rico-Fernandez, Maria; Rios-Cabrera, Reyes; Castelan, Mario; Guerrero-Reyes, Hector; Juarez-Maldonado, Antonio
A contextualized approach for segmentation of foliage in different crop species Journal Article
In: Computers and Electronics in Agriculture, vol. 156, pp. 378-386, 2019, ISSN: 0168-1699.
@article{Rico-Fernandez2019,
title = {A contextualized approach for segmentation of foliage in different crop species},
author = {Rico-Fernandez, Maria and Rios-Cabrera, Reyes and Castelan, Mario and Guerrero-Reyes, Hector and Juarez-Maldonado, Antonio},
editor = {Elsevier},
url = {https://doi.org/10.1016/j.compag.2018.11.033},
issn = {0168-1699},
year = {2019},
date = {2019-01-01},
journal = {Computers and Electronics in Agriculture},
volume = {156},
pages = {378-386},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2012
Journal Articles
Miranda-Hernandez, Jocelyn; Castelan, Mario; Torres-Mendez, Luz Abril
Face colour synthesis using partial least squares and the luminance-α-β colour transform Journal Article
In: IET Computer Vision, vol. 6, no. 4, pp. 263-272, 2012, ISBN: 1751-9632.
@article{Miranda2012,
title = {Face colour synthesis using partial least squares and the luminance-α-β colour transform},
author = {Miranda-Hernandez, Jocelyn and Castelan, Mario and Torres-Mendez, Luz Abril },
url = {http://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2011.0168},
doi = {10.1049/iet-cvi.2011.0168},
isbn = {1751-9632},
year = {2012},
date = {2012-07-01},
journal = {IET Computer Vision},
volume = {6},
number = {4},
pages = {263-272},
abstract = {For many tasks, it is necessary to synthesise realistic colour in faces from greyscale values. This is the problem the authors address in this study. Rather than propagating colour information in some regions of the image or transferring colour from an image source to a greyscale using some corresponding criterion, as many colouring systems attempt to do, they seek to synthesise facial colour information using a database of examples. This methodology is divided into two main stages. In the first stage the facial skin tone is predicted through the multiple linear regression method known as partial least squares. This regression allows to define a linear transformation between facial greyscale and colour subspaces. The second stage involves the luminance-α-β (Lαβ) colour transform which is responsible for the recovery of the fine facial detail. The core of the proposed methodology is the combination of statistical subspace analysis with the appropriate colour transform so as to produce realistic facial colourisation results in a direct manner.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
For many tasks, it is necessary to synthesise realistic colour in faces from greyscale values. This is the problem the authors address in this study. Rather than propagating colour information in some regions of the image or transferring colour from an image source to a greyscale using some corresponding criterion, as many colouring systems attempt to do, they seek to synthesise facial colour information using a database of examples. This methodology is divided into two main stages. In the first stage the facial skin tone is predicted through the multiple linear regression method known as partial least squares. This regression allows to define a linear transformation between facial greyscale and colour subspaces. The second stage involves the luminance-α-β (Lαβ) colour transform which is responsible for the recovery of the fine facial detail. The core of the proposed methodology is the combination of statistical subspace analysis with the appropriate colour transform so as to produce realistic facial colourisation results in a direct manner.
