Abstract: Skeletons are compact shape descriptions of discrete images. They have been extensively... more Abstract: Skeletons are compact shape descriptions of discrete images. They have been extensively studied because of their utility in various applications such as data compression, shape abstraction, navigation and features detection. In this article, a new Euclidean skeletal definition for 2D discrete objects based on the Distance Map (DMAT) is being proposed. As a novel feature, it is shown that this skeleton is a connected subset of the discretization of the continuous medial axis of the object....
Conferencia de la Asociacion Espanola para la Inteligencia Artificial, 2005
Abstract. This paper analyzes how to introduce machine learning algorithms into the process of di... more Abstract. This paper analyzes how to introduce machine learning algorithms into the process of direct volume rendering. A conceptual framework for the optical property function elicitation process is proposed and particularized for the use of attribute-value classifiers. The process is evaluated in terms of accuracy and speed using four different off-theshelf classifiers (J48, Nave Bayes, Simple Logistic and ECOC-Adaboost). The empirical results confirm the classification of biomedical datasets as a tough problem where an opportunity ...
The manufacturing domain is regarded as one of the most important engineering areas. Recently, sm... more The manufacturing domain is regarded as one of the most important engineering areas. Recently, smart manufacturing merges the use of sensors, intelligent controls, and software to manage each stage in the manufacturing lifecycle. Additionally, the increasing use of point clouds to model real products and machining tools in a virtual space facilitates the more accurate monitoring of the end-to-end production lifecycle. Thus, the conjunction of both, intelligent methods and more accurate 3D models allows the prediction of uncertainties and anomalies in the manufacturing process as well as reduces the final production costs. However, the high complexity of the geometrical structures defined by point clouds and the high accuracy required by the Quality Assurance/Quality control parameters during the process, pave the way for continuous improvements in smart manufacturing methods. This paper addresses a comprehensive analysis of machining tool identification utilizing temporal point clou...
International Conference in Central Europe on Computer Graphics and Visualization, 2004
Hybrid rendering of volume and polygonal model is an interesting feature of visualization systems... more Hybrid rendering of volume and polygonal model is an interesting feature of visualization systems, since it helps users to better understand the relationships between internal structures of the volume and fitted surfaces as well as external surfaces. Most of the existing bibliography focuses at the problem of correctly integrating in depth both types of information. The rendering method proposed in
International Conference on Pattern Recognition, 2000
The 3D reconstruction of the cerebral vascular anatomy can greatly improve the diagnosis of vascu... more The 3D reconstruction of the cerebral vascular anatomy can greatly improve the diagnosis of vascular pathologies, such as embolisms and haemorrhages. This paper presents a new method for the automatic extraction of the blood vessels surface and the labelling of its features, specifically branching, aneurysms and stenoses. The method works with segmented magnetic resonance angiography images. It extracts a discrete
Abstract. This paper analyzes how to introduce machine learning algorithms into the process of di... more Abstract. This paper analyzes how to introduce machine learning algorithms into the process of direct volume rendering. A conceptual framework for the optical property function elicitation process is proposed and particularized for the use of attribute-value classifiers. The process is evaluated in terms of accuracy and speed using four different off-theshelf classifiers (J48, Naıve Bayes, Simple Logistic and ECOC-Adaboost). The empirical results confirm the classification of biomedical datasets as a tough problem where an opportunity ...
This paper describes a 3D tool machining simulation system. The initial tool and the grinding whe... more This paper describes a 3D tool machining simulation system. The initial tool and the grinding wheels are integrated with the machine tool. The application reads and interprets the CNC program code that controls the machine, it computes the positions and the motion of ...
... processing. Most of the modeling and visualization systems referenced in the bibliography (Vo... more ... processing. Most of the modeling and visualization systems referenced in the bibliography (VolVis [29], 3D Viewnix [30], BOB [31]) use a quick simplified default visualization for the interaction. ... 31. ChinPurcell, K., BOB: brick of bytes. ...
Direct cell-to-cell volume visualization algorithms, also called projective rendering methods, pr... more Direct cell-to-cell volume visualization algorithms, also called projective rendering methods, present the advantage of allowing semi-transparencies and, additionally, as they project all the samples, they avoid the voxel-space aliasing. However, they are generally computationally expensive and artifacts may appear in the projection. In this paper, different projective strategies are reviewed and compared. A new algorithm, based on a back-to-front (BTF)
This paper introduces a machine learning approach into the process of direct volume rendering of ... more This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipeline process that generates the classification function within the optical property function used for rendering. Briefly, this pipeline starts with a data acquisition and selection task, it is followed by a feature extraction process, to be ended with sequence of supervised learning steps. Learning comprises Gentle Boost and CRF (Conditional Random Fields) ...
this report, a Discrete Medial Axis definition is proposed as a direct extensionof Blum's def... more this report, a Discrete Medial Axis definition is proposed as a direct extensionof Blum's definition in order to achieve a complete and compressed modelrepresentation of discrete objects which retains the significant features of theobject without introducing distorsions of its own. Moreover, it preserves theaxis connectivity and it is based on local properties of the Distance Map whichenable to design a
Abstract: Skeletons are compact shape descriptions of discrete images. They have been extensively... more Abstract: Skeletons are compact shape descriptions of discrete images. They have been extensively studied because of their utility in various applications such as data compression, shape abstraction, navigation and features detection. In this article, a new Euclidean skeletal definition for 2D discrete objects based on the Distance Map (DMAT) is being proposed. As a novel feature, it is shown that this skeleton is a connected subset of the discretization of the continuous medial axis of the object....
Conferencia de la Asociacion Espanola para la Inteligencia Artificial, 2005
Abstract. This paper analyzes how to introduce machine learning algorithms into the process of di... more Abstract. This paper analyzes how to introduce machine learning algorithms into the process of direct volume rendering. A conceptual framework for the optical property function elicitation process is proposed and particularized for the use of attribute-value classifiers. The process is evaluated in terms of accuracy and speed using four different off-theshelf classifiers (J48, Nave Bayes, Simple Logistic and ECOC-Adaboost). The empirical results confirm the classification of biomedical datasets as a tough problem where an opportunity ...
The manufacturing domain is regarded as one of the most important engineering areas. Recently, sm... more The manufacturing domain is regarded as one of the most important engineering areas. Recently, smart manufacturing merges the use of sensors, intelligent controls, and software to manage each stage in the manufacturing lifecycle. Additionally, the increasing use of point clouds to model real products and machining tools in a virtual space facilitates the more accurate monitoring of the end-to-end production lifecycle. Thus, the conjunction of both, intelligent methods and more accurate 3D models allows the prediction of uncertainties and anomalies in the manufacturing process as well as reduces the final production costs. However, the high complexity of the geometrical structures defined by point clouds and the high accuracy required by the Quality Assurance/Quality control parameters during the process, pave the way for continuous improvements in smart manufacturing methods. This paper addresses a comprehensive analysis of machining tool identification utilizing temporal point clou...
International Conference in Central Europe on Computer Graphics and Visualization, 2004
Hybrid rendering of volume and polygonal model is an interesting feature of visualization systems... more Hybrid rendering of volume and polygonal model is an interesting feature of visualization systems, since it helps users to better understand the relationships between internal structures of the volume and fitted surfaces as well as external surfaces. Most of the existing bibliography focuses at the problem of correctly integrating in depth both types of information. The rendering method proposed in
International Conference on Pattern Recognition, 2000
The 3D reconstruction of the cerebral vascular anatomy can greatly improve the diagnosis of vascu... more The 3D reconstruction of the cerebral vascular anatomy can greatly improve the diagnosis of vascular pathologies, such as embolisms and haemorrhages. This paper presents a new method for the automatic extraction of the blood vessels surface and the labelling of its features, specifically branching, aneurysms and stenoses. The method works with segmented magnetic resonance angiography images. It extracts a discrete
Abstract. This paper analyzes how to introduce machine learning algorithms into the process of di... more Abstract. This paper analyzes how to introduce machine learning algorithms into the process of direct volume rendering. A conceptual framework for the optical property function elicitation process is proposed and particularized for the use of attribute-value classifiers. The process is evaluated in terms of accuracy and speed using four different off-theshelf classifiers (J48, Naıve Bayes, Simple Logistic and ECOC-Adaboost). The empirical results confirm the classification of biomedical datasets as a tough problem where an opportunity ...
This paper describes a 3D tool machining simulation system. The initial tool and the grinding whe... more This paper describes a 3D tool machining simulation system. The initial tool and the grinding wheels are integrated with the machine tool. The application reads and interprets the CNC program code that controls the machine, it computes the positions and the motion of ...
... processing. Most of the modeling and visualization systems referenced in the bibliography (Vo... more ... processing. Most of the modeling and visualization systems referenced in the bibliography (VolVis [29], 3D Viewnix [30], BOB [31]) use a quick simplified default visualization for the interaction. ... 31. ChinPurcell, K., BOB: brick of bytes. ...
Direct cell-to-cell volume visualization algorithms, also called projective rendering methods, pr... more Direct cell-to-cell volume visualization algorithms, also called projective rendering methods, present the advantage of allowing semi-transparencies and, additionally, as they project all the samples, they avoid the voxel-space aliasing. However, they are generally computationally expensive and artifacts may appear in the projection. In this paper, different projective strategies are reviewed and compared. A new algorithm, based on a back-to-front (BTF)
This paper introduces a machine learning approach into the process of direct volume rendering of ... more This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipeline process that generates the classification function within the optical property function used for rendering. Briefly, this pipeline starts with a data acquisition and selection task, it is followed by a feature extraction process, to be ended with sequence of supervised learning steps. Learning comprises Gentle Boost and CRF (Conditional Random Fields) ...
this report, a Discrete Medial Axis definition is proposed as a direct extensionof Blum's def... more this report, a Discrete Medial Axis definition is proposed as a direct extensionof Blum's definition in order to achieve a complete and compressed modelrepresentation of discrete objects which retains the significant features of theobject without introducing distorsions of its own. Moreover, it preserves theaxis connectivity and it is based on local properties of the Distance Map whichenable to design a
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