Lesmars Lab Two patents on Point Clouds

A method for constructing a single-site laser scanning point cloud

Patent type:

(√) Invention () Utility Model () Design

Patent No:

200810047480.1

PatentsIntroduction:

The invention relates to a construction network method for a single-site Terrestrial Laser Scanning point cloud, which includes the following steps: defining a projection sphere, projecting a single-site laser scanning point cloud to a projection sphere, and constructing an initial triangular network; after a point cloud is projected, the data points are inserted into the initial Triangle network in sequence. The insertion method consists of three steps to search for triangles containing the data points to be inserted, that is, after finding the triangle where the data point to be inserted is located, connect the vertex to the three sides of the triangle to form three new triangles. Optimize the spherical lop for the locally reconstructed Triangle network; delete the six intersections of the initial triangular network, and obtain the spherical area of the projection point. The data points in the spherical area of the projection point are projected back to the original position to obtain the target area of the single-site laser scanning point cloud. The technical solution provided by the invention is of great significance in the field of reverse engineering technology, and can greatly improve the efficiency of the ground Laser Scanning Technology for object surface reconstruction.

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Storage and Real-Time Visualization of massive point cloud data

Patent type:

(√) Invention () Utility Model () Design

Patent No:

200910063372.8

Patent Overview:

Massive point cloud data storage methods, including continuous segmentation of point cloud data files and ing to process virtual address space in sequence; parsing point cloud data and storing it in memory, calculate the minimum outer box of the point cloud data. When the point cloud data in the memory exceeds the remaining memory capacity, it is stored as a multi-band image file. perform multi-band image multi-level re-sampling to build an image pyramid; repeat the preceding steps to store all the point cloud data files as multi-band images. Real-Time Visualization of massive point cloud data, including reading all multi-band images and calculating the minimum outer surround box of all point cloud data, based on the point of view to the minimum outer surround box center distance, select an appropriate level in the image pyramid for data loading, and render the loaded point cloud data. When the viewpoint moves, data Switching is performed based on the distance range of each layer of the image in the image pyramid and its corresponding level-of-level (DLE), and real-time rendering is performed.

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