نتایج جستجو برای: point cloud processing
تعداد نتایج: 1059214 فیلتر نتایج به سال:
in the last two decade the use of aerial laser scanner (als) or lidar (light detection and ranging) sensor in geomatics engineering and surveying application has augmented significantly . the main reason of the mentioned phenomenon is the reliability and accuracy of the data obtained by lidar sensors. the output of lidar is unclassified 3d point cloud. classification of the lidar point clouds i...
The high pulse frequencies of today’s airborne, mobile and terrestrial laser scanners enable the acquisition of point clouds with densities from some 20-50 points/m for airborne scanners to several thousands points/m for mobile and terrestrial scanners. For the (semi-)automated extraction of geo-information from point clouds these high point densities are very beneficial. The large number of po...
Terrain point cloud data are typically acquired through some form of Light Detection And Ranging sensing. They form a rich resource that is important in a variety of applications including navigation, line of sight, and terrain visualization. Processing terrain data has not received the attention of other forms of surface reconstruction or of image processing. The goal of terrain data processin...
In addition to the heterogeneity of aerial and terrestrial views, the small scale terrestrial point clouds are hardly comparable with large scale and overhead aerial point clouds. A hierarchical method is proposed for automatic locating of terrestrial scans in aerial point cloud. The proposed method begins with detecting the candidate positions for the deployment of the terrestrial laser scanne...
Three-dimensional (3D) point clouds are important data representations in visualization applications. The rapidly growing utility and popularity of cloud processing strongly motivate a plethora research activities on large-scale feature extraction. In this work, we investigate resampling based hypergraph signal (HGSP). We develop novel method to extract sharp object features reduce the size rep...
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