73 resultados para symbolic computation


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Spatial light modulators based around liquid crystal on silicon have found use in a variety of telecommunications applications, including the optimization of multimode fibers, free-space communications, and wavelength selective switching. Ferroelectric liquid crystals are attractive in these areas due to their fast switching times and high phase stability, but the necessity for the liquid crystal to spend equal time in each of its two possible states is an issue of practical concern. Using the highly parallel nature of a graphics processing unit architecture, it is possible to calculate DC balancing schemes of exceptional quality and stability.

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Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.