5 resultados para Blender modeling short movie rendering 3d

em Universidad de Alicante


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The availability of a large amount of observational data recently collected from magnetar outbursts is now calling for a complete theoretical study of outburst characteristics. In this Letter (the first of a series dedicated to modeling magnetar outbursts), we tackle the long-standing open issue of whether or not short bursts and glitches are always connected to long-term radiative outbursts. We show that the recent detection of short bursts and glitches seemingly unconnected to outbursts is only misleading our understanding of these events. We show that, in the framework of the starquake model, neutrino emission processes in the magnetar crust limit the temperature, and therefore the luminosity. This natural limit to the maximum luminosity makes outbursts associated with bright persistent magnetars barely detectable. These events are simply seen as a small luminosity increase over the already bright quiescent state, followed by a fast return to quiescence. In particular, this is the case for 1RXS J1708–4009, 1E 1841–045, SGR 1806–20, and other bright persistent magnetars. On the other hand, a similar event (with the same energetics) in a fainter source will drive a more extreme luminosity variation and longer cooling time, as for sources such as XTE J1810–197, 1E 1547–5408, and SGR 1627–41. We conclude that the non-detection of large radiative outbursts in connection with glitches and bursts from bright persistent magnetars is not surprising per se, nor does it need any revision of the glitches and burst mechanisms as explained by current theoretical models.

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Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six degrees of freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments.

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In the present work, a three-dimensional (3D) formulation based on the method of fundamental solutions (MFS) is applied to the study of acoustic horns. The implemented model follows and extends previous works that only considered two-dimensional and axisymmetric horn configurations. The more realistic case of 3D acoustic horns with symmetry regarding two orthogonal planes is addressed. The use of the domain decomposition technique with two interconnected sub-regions along a continuity boundary is proposed, allowing for the computation of the sound pressure generated by an acoustic horn installed on a rigid screen. In order to reduce the model discretization requirements for these cases, Green’s functions derived with the image source methodology are adopted, automatically accounting for the presence of symmetry conditions. A strategy for the calculation of an optimal position of the virtual sources used by the MFS to define the solution is also used, leading to improved reliability and flexibility of the proposed method. The responses obtained by the developed model are compared to reference solutions, computed by well-established models based on the boundary element method. Additionally, numerically calculated acoustic parameters, such as directivity and beamwidth, are compared with those evaluated experimentally.

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Today, the requirement of professional skills to university students is constantly increasing in our society. In our opinion, the content offered in official degrees need to be nourished with different variables, enriching their global professional knowledge in a parallel way; that is why, in recent years, there is a great multiplicity of complementary courses at university. One of the most socially demanded technical requirements within the architectural, design or engineering field is the management of 3D drawing software, becoming an indispensable reality in these sectors. Thus, this specific training becomes essential over two-dimension traditional design, because the inclusion of great possibilities of spatial development that go beyond conventional orthographic projections (plans, sections or elevations), allowing modelling and rotation of the selected items from multiple angles and perspectives. Therefore, this paper analyzes the teaching methodology of a complementary course for those technicians in the construction industry interested in computer-aided design, using modelling (SketchupMake) and rendering programs (Kerkythea). The course is developed from the technician point of view, by learning computer management and its application to professional development from a more general to a more specific view through practical examples. The proposed methodology is based on the development of real examples in different professional environments such as rehabilitation, new constructions, opening projects or architectural design. This multidisciplinary contribution improves criticism of students in different areas, encouraging new learning strategies and the independent development of three-dimensional solutions. Thus, the practical implementation of new situations, even suggested by the students themselves, ensures active participation, saving time during the design process and the increase of effectiveness when generating elements which may be represented, moved or virtually tested. In conclusion, this teaching-learning methodology improves the skills and competencies of students to face the growing professional demands of society. After finishing the course, technicians not only improved their expertise in the field of drawing but they also enhanced their capacity for spatial vision; both essential qualities in these sectors that can be applied to their professional development with great success.

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Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.