886 resultados para Illumination subspace
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Photovoltaic tweezers are a promising tool to place and move particles on the surface of a photovoltaic material in a controlled way. To exploit this new technique it is necessary to accurately know the electric field created by a specific illumination on the surface of the crystal and above it. This paper describes a numerical algorithm to obtain this electric field generated by several relevant light patterns, and uses them to calculate the electrophoretic potential acting over neutral, polarizable particles in the proximity of the crystal. The results are compared to experiments carried out in LiNbO3 with good overall agreement.
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Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.
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Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.
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The striking illusions produced by simultaneous brightness contrast generally are attributed to the center-surround receptive field organization of lower order neurons in the primary visual pathway. Here we show that the apparent brightness of test objects can be either increased or decreased in a predictable manner depending on how light and shadow are portrayed in the scene. This evidence suggests that perceptions of brightness are generated empirically by experience with luminance relationships, an idea whose implications we pursue in the accompanying paper.
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Mode of access: Internet.
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Bibliography: p. 283-287.
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Federal Highway Administration, Office of Research, Washington, D.C.
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"COO-2383-0077"--P. 1 of cover.
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Mode of access: Internet.
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"April 1980, issued May 1980."
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November 1978.
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"Three hundred copies ... have been printed."
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"Notes on books:" p. 256-260.
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Mode of access: Internet.
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Mode of access: Internet.