DRA. LUZ ABRIL TORRES MÉNDEZ
Profesor InvestigadorPUBLICACIONES
Para ver las publicaciones de todo Robótica y Manufactura Avanzada, ver: Publicaciones RYMA
Perez-Alcocer, R. R.; Torres-Mendez, Luz Abril; Olguin-Diaz, Ernesto; Maldonado-Ramirez, Alejandro Vision-based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions using a Model-free Robust Control Artículo de revista En: 2016. Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril Robotic Visual Tracking of Relevant Cues in Underwater Environments with Poor Visibility Conditions Artículo de revista En: Journal of Sensors, vol. 2016, 2016. Cortes-Perez, Noel; Torres-Mendez, Luz Abril A Low-Cost Mirror-Based Active Perception System for Effective Collision Free Underwater Robotic Navigation Artículo de revista En: 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 61-68, 2016. Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril; Castelan, Mario A bag of relevant regions for visual place recognition in challenging environments Conferencia 2016 23rd International Conference on Pattern Recognition (ICPR), 2016. Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril A Bag of Relevant Regions Model for Place Recognition in Coral Reefs Conferencia OCEANS 2016, IEEE 2016. Maldonado-Ramirez, Alejandro; Torres-Méndez, Luz Abril A bag of relevant regions model for visual place recognition in coral reefs Proceedings Article En: OCEANS 2016 MTS/IEEE Monterey, pp. 1-5, 2016. Ponce-Hinestroza, A. N.; Torres-Mendez, Luz Abril; Drews, Paulo A statistical learning approach for underwater color restoration with adaptive training based on visual attention Proceedings Article En: OCEANS 2016 MTS/IEEE Monterey, pp. 1-6, 2016. Ponce-Hinestroza, A-N; Torres-Mendez, Luz Abril; Drews, Paulo A statistical learning approach for underwater color restoration with adaptive training based on visual attention Proceedings Article En: OCEANS 2016 MTS/IEEE Monterey, pp. 1–6, IEEE 2016. Ponce-Hinestroza, A-N; Torres-Mendez, Luz Abril; Drews, Paulo Using a MRF-BP Model with Color Adaptive Training for Underwater Color Restoration Proceedings Article En: ICPR 2016 IEEE Cancun, pp. 1–6, IEEE 2016. Castelan, Mario; Cruz-Perez, Elier; Torres-Mendez, Luz Abril A Photometric Sampling Strategy for Reflectance Characterization and Transference Artículo de revista En: Computación y Sistemas, vol. 19, no 2, pp. 255-272, 2015. Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril; Rodriguez-Telles, Francisco G Ethologically inspired reactive exploration of coral reefs with collision avoidance: Bridging the gap between human and robot spatial understanding of unstructured environments Conferencia Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, IEEE 2015. Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril Autonomous robotic exploration of coral reefs using a visual attention-driven strategy for detecting and tracking regions of interest Conferencia OCEANS 2015-Genova, IEEE 2015. Romero-Martínez, C. E.; Torres-Mendez, Luz Abril; Martinez-Garcia, Edgar A. Modeling motor-perceptual behaviors to enable intuitive paths in an aquatic robot Proceedings Article En: OCEANS 2015 - MTS/IEEE Washington, pp. 1-5, 2015. Labastida-Valdés, L.; Torres-Mendez, Luz Abril; Hutchinson, S. A. Using the motion perceptibility measure to classify points of interest for visual-based AUV guidance in a reef ecosystem Proceedings Article En: OCEANS 2015 - MTS/IEEE Washington, pp. 1-6, 2015. González-García, Luis C.; Torres-Mendez, Luz Abril; Martínez, Julieta; Sattar, Junaed; Little, James Are You Talking to Me? Detecting Attention in First-Person Interactions Proceedings Article En: pp. 137-142, 2015, ISSN: 2308-4197. Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril using supercolor-pixels descriptors for tracking relevant cues in underwater environments with poor visibility conditions Proceedings Article En: ICRA 2015 Workshop on Visual Place Recognition in Changing Environmen ts, 2015. Martinez-Garcia, Edgar A.; Torres-Mendez, Luz Abril; Elara Mohan, Rajesh Multi-legged robot dynamics navigation model with optical flow Artículo de revista En: International Journal of Intelligent Unmanned Systems, vol. 2, no 2, pp. 121-139, 2014. Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril; Martinez-Garcia, Edgar A. Robust detection and tracking of regions of interest for autonomous underwater robotic exploration Conferencia Proc. 6th Int. Conf. on Advanced Cognitive Technologies and Applications, 2014. Rodriguez-Telles, Francisco G; Perez-Alcocer, Ricardo; Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril; Bikram Dey, Bir; Martinez-Garcia, Edgar A. Vision-based reactive autonomous navigation with obstacle avoidance: Towards a non-invasive and cautious exploration of marine habitat Conferencia 2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE 2014. Rodríguez-Teiles, F. G.; Perez-Alcocer, Ricardo; Maldonado-Ramirez, Alejandro; Torres-Mendez, Luz Abril; Dey, B. B.; Martinez-Garcia, Edgar A. Vision-based reactive autonomous navigation with obstacle avoidance: Towards a non-invasive and cautious exploration of marine habitat Proceedings Article En: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 3813-3818, 2014, ISSN: 1050-4729. Rivero-Juarez, Joaquin; Martinez-Garcia, Edgar A.; Torres-Mendez, Luz Abril; Elara Mohan, Rajesh 3D Heterogeneous Multi-sensor Global Registration Artículo de revista En: Procedia Engineering, vol. 64, pp. 1552 - 1561, 2013, ISSN: 1877-7058. Miranda-Hernandez, Jocelyn; Castelan, Mario; Torres-Mendez, Luz Abril Face colour synthesis using partial least squares and the luminance-α-β colour transform Artículo de revista En: IET Computer Vision, vol. 6, no 4, pp. 263-272, 2012, ISBN: 1751-9632. Torres-Mendez, Luz Abril; Ramirez-Sosa Moran, Marco I; Castelan, Mario A Single-Frame Super-Resolution Innovative Approach Conferencia MICAI 2007: Advances in Artificial Intelligence: 6th Mexican International Conference on Artificial Intelligence, Aguascalientes, Mexico, November 4-10, 2007. Proceedings, Springer Berlin Heidelberg, Berlin, Heidelberg, 2007, ISBN: 978-3-540-76631-5. Castelan, Mario; Almazan-Delfin, Ana Judith; Ramirez-Sosa Moran, Marco I; Torres-Mendez, Luz Abril Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal Conferencia MICAI 2007: Advances in Artificial Intelligence: 6th Mexican International Conference on Artificial Intelligence, Aguascalientes, Mexico, November 4-10, 2007. Proceedings, Springer Berlin Heidelberg, Berlin, Heidelberg, 2007, ISBN: 978-3-540-76631-5.2016
Artículos de revista
@article{P\'{e}rez-Alcocer2016,
title = {Vision-based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions using a Model-free Robust Control},
author = {Perez-Alcocer, R. R. and Torres-Mendez, Luz Abril and Olguin-Diaz, Ernesto and Maldonado-Ramirez, Alejandro },
year = {2016},
date = {2016-06-06},
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pubstate = {published},
tppubtype = {article}
}
@article{maldonado2016robotic,
title = {Robotic Visual Tracking of Relevant Cues in Underwater Environments with Poor Visibility Conditions},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril},
url = {https://www.hindawi.com/journals/js/2016/4265042/},
year = {2016},
date = {2016-01-01},
journal = {Journal of Sensors},
volume = {2016},
publisher = {Hindawi Publishing Corporation},
abstract = {Using visual sensors for detecting regions of interest in underwater environments is fundamental for many robotic applications. Particularly, for an autonomous exploration task, an underwater vehicle must be guided towards features that are of interest. If the relevant features can be seen from the distance, then smooth control movements of the vehicle are feasible in order to position itself close enough with the final goal of gathering visual quality images. However, it is a challenging task for a robotic system to achieve stable tracking of the same regions since marine environments are unstructured and highly dynamic and usually have poor visibility. In this paper, a framework that robustly detects and tracks regions of interest in real time is presented. We use the chromatic channels of a perceptual uniform color space to detect relevant regions and adapt a visual attention scheme to underwater scenes. For the tracking, we associate with each relevant point superpixel descriptors which are invariant to changes in illumination and shape. The field experiment results have demonstrated that our approach is robust when tested on different visibility conditions and depths in underwater explorations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{Cortx00E9sPx00E9rez2016ALM,
title = {A Low-Cost Mirror-Based Active Perception System for Effective Collision Free Underwater Robotic Navigation},
author = {Cortes-Perez, Noel and Torres-Mendez, Luz Abril},
year = {2016},
date = {2016-01-01},
journal = {2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
pages = {61-68},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Conferencias
@conference{7899826,
title = {A bag of relevant regions for visual place recognition in challenging environments},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril and Castelan, Mario},
doi = {10.1109/ICPR.2016.7899826},
year = {2016},
date = {2016-12-01},
booktitle = {2016 23rd International Conference on Pattern Recognition (ICPR)},
pages = {1358-1363},
abstract = {In this paper, we present a method for vision-based place recognition in environments with a high content of similar features and that are prone to variations in illumination. The high similarity of features makes difficult the disambiguation between two different places. The novelty of our method relies on using the Bag of Words (BoW) approach to derive an image descriptor from a set of relevant regions, which are extracted using a visual attention algorithm. We name our approach Bag of Relevant Regions (BoRR). The descriptor of each relevant region is built by using a 2D histogram of the chromatic channels of the CIE-Lab color space. We have compared our results with those using state of the art descriptors that include the BoW and demonstrate that our approach performs better in most of the cases.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
@conference{maldonado2016bag,
title = {A Bag of Relevant Regions Model for Place Recognition in Coral Reefs},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril },
year = {2016},
date = {2016-01-01},
booktitle = {OCEANS 2016},
pages = {1--5},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Proceedings Articles
@inproceedings{7761188,
title = {A bag of relevant regions model for visual place recognition in coral reefs},
author = {Maldonado-Ramirez, Alejandro and Torres-M\'{e}ndez, Luz Abril},
doi = {10.1109/OCEANS.2016.7761188},
year = {2016},
date = {2016-09-01},
booktitle = {OCEANS 2016 MTS/IEEE Monterey},
pages = {1-5},
abstract = {Vision-based place recognition in underwater environments is a key component for autonomous robotic exploration. However, this task can be very challenging due to the inherent properties of this kind of places such as: color distortion, poor visibility, perceptual aliasing and dynamic illumination. In this paper, we present a method for vision-based place recognition in coral reefs. Our method relies on using the Bag-of-Words (BoW) approach to derive a descriptor, for the whole image, from a set of relevant regions, which are extracted by utilizing a visual attention algorithm. The descriptor for each relevant region is built by using an histogram of the chromatic channels of the CIE-Lab color space. We present results of our method for a place recognition task in real life videos as well as comparisons of our method against other popular techniques. It can be seen that our approach performs better in most of the cases.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{7761187,
title = {A statistical learning approach for underwater color restoration with adaptive training based on visual attention},
author = {Ponce-Hinestroza, A. N. and Torres-Mendez, Luz Abril and Drews, Paulo},
doi = {10.1109/OCEANS.2016.7761187},
year = {2016},
date = {2016-09-01},
booktitle = {OCEANS 2016 MTS/IEEE Monterey},
pages = {1-6},
abstract = {In most artificial vision systems the quality of acquired images is directly related with the amount of information that can be obtained from them, and, particularly in underwater robotics applications involving monitoring and inspection tasks this is crucial. Statistical learning methods like Markov Random Fields with Belief Propagation (MRF-BP) provide a solution by using existing essential correlations in training sets. However, as in any restoration/correction method for real applications, it is not possible to have color ground truth available on-line. In this paper, we present a MRF-BP model formulated in the chromatic domain of underwater scenes such that we synthesize the ground truth color to train the model and maximize the capabilities of our method. The generated ground truth introduces some improvements to existing color correction methods and visual attention considerations which also helps to choose a small size training set for the MRF-BP model. Feasibility of our approach is shown from the results in which a good color discrimination is observed even in poor visibility conditions.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{ponce2016oceansb,
title = {A statistical learning approach for underwater color restoration with adaptive training based on visual attention},
author = {Ponce-Hinestroza, A-N and Torres-Mendez, Luz Abril and Drews, Paulo },
year = {2016},
date = {2016-01-01},
booktitle = {OCEANS 2016 MTS/IEEE Monterey},
pages = {1--6},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{ponce2016icpr,
title = {Using a MRF-BP Model with Color Adaptive Training for Underwater Color Restoration},
author = {Ponce-Hinestroza, A-N and Torres-Mendez, Luz Abril and Drews, Paulo},
year = {2016},
date = {2016-01-01},
booktitle = {ICPR 2016 IEEE Cancun},
pages = {1--6},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2015
Artículos de revista
@article{Castelan2015,
title = {A Photometric Sampling Strategy for Reflectance Characterization and Transference},
author = {Castelan, Mario and Cruz-Perez, Elier and Torres-Mendez, Luz Abril},
url = {http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/1944},
year = {2015},
date = {2015-01-01},
journal = {Computaci\'{o}n y Sistemas},
volume = {19},
number = {2},
pages = {255-272},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Conferencias
@conference{maldonado2015ethologically,
title = {Ethologically inspired reactive exploration of coral reefs with collision avoidance: Bridging the gap between human and robot spatial understanding of unstructured environments},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril and Rodriguez-Telles, Francisco G},
year = {2015},
date = {2015-01-01},
booktitle = {Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on},
pages = {4872--4879},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
@conference{maldonado2015autonomous,
title = {Autonomous robotic exploration of coral reefs using a visual attention-driven strategy for detecting and tracking regions of interest},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril
},
year = {2015},
date = {2015-01-01},
booktitle = {OCEANS 2015-Genova},
pages = {1--5},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Proceedings Articles
@inproceedings{7404424,
title = {Modeling motor-perceptual behaviors to enable intuitive paths in an aquatic robot},
author = {Romero-Mart\'{i}nez, C. E. and Torres-Mendez, Luz Abril and Martinez-Garcia, Edgar A.},
url = {http://ieeexplore.ieee.org/document/7404424/},
doi = {10.23919/OCEANS.2015.7404424},
year = {2015},
date = {2015-10-01},
booktitle = {OCEANS 2015 - MTS/IEEE Washington},
pages = {1-5},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{7404605,
title = {Using the motion perceptibility measure to classify points of interest for visual-based AUV guidance in a reef ecosystem},
author = {Labastida-Vald\'{e}s, L. and Torres-Mendez, Luz Abril and Hutchinson, S. A.},
url = {http://ieeexplore.ieee.org/document/7404605/},
doi = {10.23919/OCEANS.2015.7404605},
year = {2015},
date = {2015-10-01},
booktitle = {OCEANS 2015 - MTS/IEEE Washington},
pages = {1-6},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{Gonz\'{a}lez-Garc\'{i}a2015,
title = {Are You Talking to Me? Detecting Attention in First-Person Interactions},
author = {Gonz\'{a}lez-Garc\'{i}a, Luis C. and Torres-Mendez, Luz Abril and Mart\'{i}nez, Julieta and Sattar, Junaed and Little, James},
url = {https://www.researchgate.net/publication/274065286_Are_You_Talking_to_Me_Detecting_Attention_in_First-Person_Interactions},
issn = {2308-4197},
year = {2015},
date = {2015-00-00},
pages = { 137-142},
abstract = {This paper presents an approach for a mobile robot to detect the level of attention of a human in first-person interactions. Determining the degree of attention is an essential task in day-today interactions. In particular, we are interested in natural Human-Robot Interactions (HRI's) during which a robot needs to estimate the focus and the degree of the user's attention to determine the most appropriate moment to initiate, continue and terminate an interaction. Our approach is novel in that it uses a linear regression technique to classify raw depth-image data according to three levels of user attention on the robot (null, partial and total). This is achieved by measuring the linear independence of the input range data with respect to a dataset of user poses. We overcome the problem of time overhead that a large database can add to real-time Linear Regression Classification (LRC) methods by including only the feature vectors with the most relevant information. We demonstrate the approach by presenting experimental data from human-interaction studies with a PR2 robot. Results demonstrate our attention classifier to be accurate and robust in detecting the attention levels of human participants. I. INTRODUCTION Determining the attention of people is an essential component of day-today interactions. We are constantly monitoring other people's gaze, head and body poses while engaged in a conversation [1][2][3]. We also perform attention estimation in order to perform natural interactions [4][5]. In short, attention estimation is a fundamental component of effective social interaction; therefore, for robots to be efficient social agents it is necessary to provide them with reliable mechanisms to estimate human attention. We believe that human attention estimation, particularly in the context of interactions, is highly subjective. However, attempts to model it have been relatively successful, e.g., allowing a robot to ask for directions when it finds a human, as in the work of Weiss et al. [6]. Nonetheless, the state-of-the-art is still far from reaching a point where a robot can successfully interact with humans without relying on mechanisms not common to natural language. Recently, the use of range images to make more natural human-machine interfaces has been in the agenda of researchers, like in the case of the Microsoft Kinect TM , which delivers a skeleton of
Are You Talking to Me? Detecting Attention in First-Person Interactions (PDF Download Available). Available from: https://www.researchgate.net/publication/274065286_Are_You_Talking_to_Me_Detecting_Attention_in_First-Person_Interactions [accessed Jun 17, 2017].},
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pubstate = {published},
tppubtype = {inproceedings}
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Are You Talking to Me? Detecting Attention in First-Person Interactions (PDF Download Available). Available from: https://www.researchgate.net/publication/274065286_Are_You_Talking_to_Me_Detecting_Attention_in_First-Person_Interactions [accessed Jun 17, 2017].@inproceedings{Maldonao-Ramirez2015,
title = {using supercolor-pixels descriptors for tracking relevant cues in underwater environments with poor visibility conditions},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril},
year = {2015},
date = {2015-00-00},
publisher = {ICRA 2015 Workshop on Visual Place Recognition in Changing Environmen ts},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2014
Artículos de revista
@article{doi:10.1108/IJIUS-04-2014-0003,
title = {Multi-legged robot dynamics navigation model with optical flow},
author = {Martinez-Garcia, Edgar A. and Torres-Mendez, Luz Abril and Elara Mohan, Rajesh },
url = {http://dx.doi.org/10.1108/IJIUS-04-2014-0003},
doi = {10.1108/IJIUS-04-2014-0003},
year = {2014},
date = {2014-01-01},
journal = {International Journal of Intelligent Unmanned Systems},
volume = {2},
number = {2},
pages = {121-139},
abstract = {Purpose \textendash The purpose of this paper is to establish analytical and numerical solutions of a navigational law to estimate displacements of hyper-static multi-legged mobile robots, which combines: monocular vision (optical flow of regional invariants) and legs dynamics. Design/methodology/approach \textendash In this study the authors propose a Euler-Lagrange equation that control legs’ joints to control robot's displacements. Robot's rotation and translational velocities are feedback by motion features of visual invariant descriptors. A general analytical solution of a derivative navigation law is proposed for hyper-static robots. The feedback is formulated with the local speed rate obtained from optical flow of visual regional invariants. The proposed formulation includes a data association algorithm aimed to correlate visual invariant descriptors detected in sequential images through monocular vision. The navigation law is constrained by a set of three kinematic equilibrium conditions for navigational scenarios: constant acceleration, constant velocity, and instantaneous acceleration. Findings \textendash The proposed data association method concerns local motions of multiple invariants (enhanced MSER) by minimizing the norm of multidimensional optical flow feature vectors. Kinematic measurements are used as observable arguments in the general dynamic control equation; while the legs joints dynamics model is used to formulate the controllable arguments. Originality/value \textendash The given analysis does not combine sensor data of any kind, but only monocular passive vision. The approach automatically detects environmental invariant descriptors with an enhanced version of the MSER method. Only optical flow vectors and robot's multi-leg dynamics are used to formulate descriptive rotational and translational motions for self-positioning.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Conferencias
@conference{maldonado2014robust,
title = {Robust detection and tracking of regions of interest for autonomous underwater robotic exploration},
author = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril and Martinez-Garcia, Edgar A.},
year = {2014},
date = {2014-01-01},
booktitle = {Proc. 6th Int. Conf. on Advanced Cognitive Technologies and Applications},
pages = {165--171},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
@conference{rodriguez2014vision,
title = {Vision-based reactive autonomous navigation with obstacle avoidance: Towards a non-invasive and cautious exploration of marine habitat},
author = {Rodriguez-Telles, Francisco G and Perez-Alcocer, Ricardo and Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril and Bikram Dey, Bir and Martinez-Garcia, Edgar A.},
year = {2014},
date = {2014-01-01},
booktitle = {2014 IEEE International Conference on Robotics and Automation (ICRA)},
pages = {3813--3818},
organization = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Proceedings Articles
@inproceedings{6907412,
title = {Vision-based reactive autonomous navigation with obstacle avoidance: Towards a non-invasive and cautious exploration of marine habitat},
author = {Rodr\'{i}guez-Teiles, F. G. and Perez-Alcocer, Ricardo and Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril and Dey, B. B. and Martinez-Garcia, Edgar A.},
url = {http://ieeexplore.ieee.org/document/6907412/},
doi = {10.1109/ICRA.2014.6907412},
issn = {1050-4729},
year = {2014},
date = {2014-05-01},
booktitle = {2014 IEEE International Conference on Robotics and Automation (ICRA)},
pages = {3813-3818},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2013
Artículos de revista
@article{RIVEROJUAREZ20131552,
title = {3D Heterogeneous Multi-sensor Global Registration},
author = {Rivero-Juarez, Joaquin and Martinez-Garcia, Edgar A. and Torres-Mendez, Luz Abril and Elara Mohan, Rajesh },
url = {http://www.sciencedirect.com/science/article/pii/S1877705813017517},
doi = {http://dx.doi.org/10.1016/j.proeng.2013.09.237},
issn = {1877-7058},
year = {2013},
date = {2013-01-01},
journal = {Procedia Engineering},
volume = {64},
pages = {1552 - 1561},
abstract = {This manuscript presents a deterministic model to register heterogeneous 3D data arising from a ring of eight ultrasonic sonar, one high data density LiDAR (light detection and ranging), and a semi-ring of three visual sensors. The three visual sensors are arranged in a cylindrical ring, and although they provide 2D colour images, a radial multi-stereo geometric model is proposed to yield 3D data. All deployed sensors are geometrically placed on-board a wheeled mobile robot platform, and data registration is carried out navigating indoors. The sensor devices in discussion are coordinated and synchronized by a home-made distributed sensor suite system. Mathematical deterministic formulation for data registration is used to obtain experimental and numerical results on global mapping. Data registration relies on a geometric model to compute depth information from a semi- circular trinocular stereo sensor that is proposed to rectify and calibrate three image frames with different orientations and positions, but with same projection point.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2012
Artículos de revista
@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}
}
2007
Conferencias
@conference{Torres-M\'{e}ndez2007,
title = {A Single-Frame Super-Resolution Innovative Approach},
author = {Torres-Mendez, Luz Abril and Ramirez-Sosa Moran, Marco I and Castelan, Mario },
editor = {Gelbukh, Alexander
and Kuri Morales, Angel Fernando},
url = {http://dx.doi.org/10.1007/978-3-540-76631-5_61},
doi = {10.1007/978-3-540-76631-5_61},
isbn = {978-3-540-76631-5},
year = {2007},
date = {2007-01-01},
booktitle = {MICAI 2007: Advances in Artificial Intelligence: 6th Mexican International Conference on Artificial Intelligence, Aguascalientes, Mexico, November 4-10, 2007. Proceedings},
pages = {640--649},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
@conference{Castel\'{a}n2007b,
title = {Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal},
author = {Castelan, Mario and Almazan-Delfin, Ana Judith and Ramirez-Sosa Moran, Marco I and Torres-Mendez, Luz Abril },
editor = {Gelbukh, Alexander
and Kuri Morales, Angel Fernando},
url = {http://dx.doi.org/10.1007/978-3-540-76631-5_72},
doi = {10.1007/978-3-540-76631-5_72},
isbn = {978-3-540-76631-5},
year = {2007},
date = {2007-01-01},
booktitle = {MICAI 2007: Advances in Artificial Intelligence: 6th Mexican International Conference on Artificial Intelligence, Aguascalientes, Mexico, November 4-10, 2007. Proceedings},
pages = {758--768},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
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