903 resultados para 3D-annotation


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[EN] In this paper we present a variational technique for the reconstruction of 3D cylindrical surfaces. Roughly speaking by a cylindrical surface we mean a surface that can be parameterized using the projection on a cylinder in terms of two coordinates, representing the displacement and angle in a cylindrical coordinate system respectively. The starting point for our method is a set of different views of a cylindrical surface, as well as a precomputed disparity map estimation between pair of images. The proposed variational technique is based on an energy minimization where we balance on the one hand the regularity of the cylindrical function given by the distance of the surface points to cylinder axis, and on the other hand, the distance between the projection of the surface points on the images and the expected location following the precomputed disparity map estimation between pair of images. One interesting advantage of this approach is that we regularize the 3D surface by means of a bi-dimensio al minimization problem. We show some experimental results for large stereo sequences.

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[EN] In this paper, we present a vascular tree model made with synthetic materials and which allows us to obtain images to make a 3D reconstruction.We have used PVC tubes of several diameters and lengths that will let us evaluate the accuracy of our 3D reconstruction. In order to calibrate the camera we have used a corner detector. Also we have used Optical Flow techniques to follow the points through the images going and going back. We describe two general techniques to extract a sequence of corresponding points from multiple views of an object. The resulting sequence of points will be used later to reconstruct a set of 3D points representing the object surfaces on the scene. We have made the 3D reconstruction choosing by chance a couple of images and we have calculated the projection error. After several repetitions, we have found the best 3D location for the point.

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[EN] In this paper we present a method for the regularization of 3D cylindrical surfaces. By a cylindrical surface we mean a 3D surface that can be expressed as an application S(l; µ) ! R3 , where (l; µ) represents a cylindrical parametrization of the 3D surface. We built an initial cylindrical parametrization of the surface. We propose a new method to regularize such cylindrical surface. This method takes into account the information supplied by the disparity maps computed between pair of images to constraint the regularization of the set of 3D points. We propose a model based on an energy which is composed of two terms: an attachment term that minimizes the difference between the image coordinates and the disparity maps and a second term that enables a regularization by means of anisotropic diffusion. One interesting advantage of this approach is that we regularize the 3D surface by using a bi-dimensional minimization problem.

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[EN] In this paper, we present a vascular tree model made with synthetic materials and which allows us to obtain images to make a 3D reconstruction. In order to create this model, we have used PVC tubes of several diameters and lengths that will let us evaluate the accuracy of our 3D reconstruction. We have made the 3D reconstruction from a series of images that we have from our model and after we have calibrated the camera. In order to calibrate it we have used a corner detector. Also we have used Optical Flow techniques to follow the points through the images going and going back. Once we have the set of images where we have located a point, we have made the 3D reconstruction choosing by chance a couple of images and we have calculated the projection error. After several repetitions, we have found the best 3D location for the point.

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[EN] In the last years we have developed some methods for 3D reconstruction. First we began with the problem of reconstructing a 3D scene from a stereoscopic pair of images. We developed some methods based on energy functionals which produce dense disparity maps by preserving discontinuities from image boundaries. Then we passed to the problem of reconstructing a 3D scene from multiple views (more than 2). The method for multiple view reconstruction relies on the method for stereoscopic reconstruction. For every pair of consecutive images we estimate a disparity map and then we apply a robust method that searches for good correspondences through the sequence of images. Recently we have proposed several methods for 3D surface regularization. This is a postprocessing step necessary for smoothing the final surface, which could be afected by noise or mismatch correspondences. These regularization methods are interesting because they use the information from the reconstructing process and not only from the 3D surface. We have tackled all these problems from an energy minimization approach. We investigate the associated Euler-Lagrange equation of the energy functional, and we approach the solution of the underlying partial differential equation (PDE) using a gradient descent method.

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[EN] In this paper we present a method for the regularization of a set of unstructured 3D points obtained from a sequence of stereo images. This method takes into account the information supplied by the disparity maps computed between pairs of images to constraint the regularization of the set of 3D points. We propose a model based on an energy which is composed of two terms: an attachment term that minimizes the distance from 3D points to the projective lines of camera points, and a second term that allows for the regularization of the set of 3D points by preserving discontinuities presented on the disparity maps. We embed this energy in a 2D finite element method. After minimizing, this method results in a large system of equations that can be optimized for fast computations. We derive an efficient implicit numerical scheme which reduces the number of calculations and memory allocations.

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[ES] Se analizan las posibilidades del Image based modeling (IBM), como técnica de escaneado 3D de bajo coste para la modelización de inscripciones romanas, a partir del trabajo realizado en el Museo Arqueológico Nacional de Madrid sobre una amplia tipología de soportes epigráficos (piedra, bronce, arcilla), con resultados óptimos para la catalogación, estudio y difusión de este tipo de documentación histórica. Los resultados obtenidos permiten obtener inscripciones romanas en 3D que se pueden incorporar a los proyectos de epigrafía digital en curso, permitiendo su acceso a través de ordenadores y dispositivos móviles, sin coste añadido para los investigadores.

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[ES] COMO (Cooperative Modeller) es un software de modelado 3D colaborativo. Siguiendo una arquitectura cliente-servidor, este software permite que múltiples usuarios se conecten a través de la red y tabajen, en tiempo real, sobre la misma escena 3D. Las principales funcionalidades de COMO incluyen la creación de primitivas geométricas (cubos, conos, cilindros y esferas), el importado de mallas desde fichero (.obj), la transfrmación de selecciones de objetos (traslaciones, rotaciones y escalados), la creación de múltiples luces direccionales, la edición de materiales, o la aplicación de texturas a ciertas mallas. Aunque actualmente COMO se encuentra únicamente disponible para Ubuntu, el proyecto se ha realizado con una visión plataforma. Por esta razón, se ha empleado tecnologías y librerías multiplataforma como OpenGL, Qt o Boost, de manera que se facilite el portado del software a otras plataformas en el futuro.

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[ES] El siguiente trabajo de fin de grado consiste en el análisis, desarrollo e implementación de una pequeña parte de un  videojuego, que tiene como título Darkest Nights, que se basa en la defensa de una plataforma, haciendo uso del motor gráfico Unity 3D. Con este trabajo se pretenden analizar los distintos componentes que influyen en el proceso de desarrollo e implementación del mismo, haciendo uso de distintas herramientas como, el canvas gamificado o una ficha de concepto que nos permitan definir y establecer un conjunto de características que nos servirán como punto de partida, desde el cual podremos identificar desde una temprana fase las partes más importantes y que requerirán más atención del videojuego. Dentro de este proyecto también se pretende realizar la implementación de distintos tipos de controles de un jugador en un entorno 3D, el jugador debe realizar distintas acciones como moverse, esquivar y atacar a sus enemigos para defender con éxito una plataforma. Estos controles se implementaran con la finalidad de analizar y evaluar su viabilidad en las pantallas táctiles de los dispositivos móviles. En concreto se realiza la implementación y explicación de 4 tipos distintos de controles donde se comentan sus  ventajas, desventajas y las sensaciones que causaban en los jugadores, llevándonos a sacar conclusiones que nos permitían mejorar las siguientes implementaciones.  Además se explica con detalle la generación de personajes y enemigos en 3D con sus respectivas animaciones, explicando los distintos componentes necesarios para su implementación, al igual que la lógica básica necesaria para que sigan un determinado comportamiento.

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Los avances experimentados en los últimos años en las tecnologías basadas en el procesamiento de las fotografías digitales, permite abordar proyectos de modelización 3D de inscripciones romanas, como el realizado en el Museo Arqueológico Nacional (Madrid). La utilización de esta tecnología innovadora aporta a los especialistas mejores reproducciones que la fotografía convencional, que supondrán un enriquecimiento de las bases de datos epigráficas, pero su utilidad se extiende también a la propia enseñanza de la Epigrafía.

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In the present study, a new pushover procedure for 3D frame structures is proposed, based on the application of a set of horizontal force and torque distributions at each floor level; in order to predict the most severe configurations of an irregular structure subjected to an earthquake, more than one pushover analysis has to be performed. The proposed method is validated by a consistent comparison of results from static pushover and dynamic simulations in terms of different response parameters, such as displacements, rotations, floor shears and floor torques. Starting from the linear analysis, the procedure is subsequently extended to the nonlinear case. The results confirm the effectiveness of the proposed procedure to predict the structural behaviour in the most severe configurations.

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The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe