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Luana Valentini Maria Antonia Brovelli Giorgio Zamboni 《International Journal of Digital Earth》2014,7(4):336-350
In this article, we present the realisation of a multi-frame and multi-dimensional WebGIS that allows users to simultaneously analyse a specific portion of the Earth taking into account the historical information, too. Two graphical panels have been realised: one for the usual 2D view and one for a more realistic 3D view. Both panels display historical maps of the city, the current orthophoto and the digital topographical map. The 3D frame is based on NASA World Wind, an open source virtual globe from where 3D buildings are shown extruding the 2D shapes using their mean height. Thanks to a specifically designed graphical user interface, it is also possible to dynamically thematise the buildings on the globe according to different criteria (e.g. the construction time span) so that only the geometries fulfilling the request are turned on. Within the proposed application, a synchronisation between the two panels has been implemented, in order to maintain a constant alignment of the two viewers. The application is also open to the time dimension. In fact, assigning to each geometry two dates (e.g. ‘year of construction’ and ‘year of demolition’), it is possible to dynamically view how buildings have changed over time, both in their shape and height. Future developments of this work will concern the possibility of implementing a city model with a higher level of detail. 相似文献
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提升目标检测模型的泛化能力是计算机视觉领域的研究热点和关键难点。本文提出了一种Multi-Patch方法和多帧增量式预测策略,提升了不同场景下交通视频目标检测的稳健性,有效解决了目标尺度多变导致的视频中目标召回率低的问题。根据视频分辨率和目标尺寸,基于Multi-Patch方法自动将视频帧分割成最佳输入尺寸,使用YOLO v4神经网络并关联连续帧的上下文信息,采用增量式预测策略降低视频目标检测的漏检率,提升不同场景下视频目标的检测置信度得分和召回率。采集不同拍摄条件下的交通视频,验证该方法的有效性。试验结果表明,本文提出的目标检测方法召回率在80%以上,置信度平均得分在0.84以上。 相似文献
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