17 resultados para Variational Convergence


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The aim of this paper is to present the experience of using lecture recordings to support curriculum changes within the framework of the European convergence process, mainly courses that need to be promoted or discontinued. We will explain an integrated solution for recording lectures consisting of a web portal, a videoconferencing tool and an economical and easily transportable kit. The validation process was performed recording three different courses at the Universidad Politécnica of Madrid (UPM) and using different diffusion channels, such as Moodle, an open source web portal called GlobalPlaza that supports streaming and recordings and the YouTube UPM channel. To assess the efficiency of our solution, a formal evaluation was conducted and will be also presented in this paper. The results show that lecture recordings allow teachers to support discontinued and new courses and enable students from remote areas to participate in international educational programmes, also the resulting recordings will be used as learning objects for future virtual courses.

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Validating modern oceanographic theories using models produced through stereo computer vision principles has recently emerged. Space-time (4-D) models of the ocean surface may be generated by stacking a series of 3-D reconstructions independently generated for each time instant or, in a more robust manner, by simultaneously processing several snapshots coherently in a true ?4-D reconstruction.? However, the accuracy of these computer-vision-generated models is subject to the estimations of camera parameters, which may be corrupted under the influence of natural factors such as wind and vibrations. Therefore, removing the unpredictable errors of the camera parameters is necessary for an accurate reconstruction. In this paper, we propose a novel algorithm that can jointly perform a 4-D reconstruction as well as correct the camera parameter errors introduced by external factors. The technique is founded upon variational optimization methods to benefit from their numerous advantages: continuity of the estimated surface in space and time, robustness, and accuracy. The performance of the proposed algorithm is tested using synthetic data produced through computer graphics techniques, based on which the errors of the camera parameters arising from natural factors can be simulated.