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《Intelligent Computer and Applications》 2019-04
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Research on parallel simplification of road surface point cloud

SUN Dalin;TANG Haoxuan;School of Computer Science and Technology,Harbin Institute of Technology;  
To effectively solve the problem of time delay in the simplification of large-scale road surface laser point cloud,accurately reserving the feature points while accelerating the simplification process,a simplification algorithm based on slope difference of the scanning line point cloud and two parallel acceleration methods are studied. Firstly,based on the distribution characteristics of point cloud of road surface scan line,the slope difference of the line between adjacent points is taken as the benchmark to identify feature points,and a serial simplification algorithm is implemented. At the same time,based on the study of the algorithm flowand the extraction of parallel steps,the parallel simplification algorithm using multi-core CPU and the parallel simplification algorithm using GPU are designed and implemented. The former relies on OpenMP technology to achieve a multi-threaded parallelism; the latter is implemented under the CUDA framework,which belongs to the heterogeneous parallel computing combining CPU and GPU. In the experimental stage,the effectiveness of the algorithm is verified on the actual road surface point cloud. Meanwhile,The performance tests of three algorithms on point cloud data of different scales are designed. By plotting the performance curve,the advantages and disadvantages of the two parallel algorithms are analyzed and compared. The final realization of the parallel simplification algorithm based on GPU has achieved a speedup about 100 compared to the serial algorithm.
【CateGory Index】: U418.4;TP332
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