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OpenCL-accelerated Point Feature Histogram and Its Application in Railway Track Point Cloud Data Processing

Dongxu Lv, Peijun Wang, Wentao Li, Peng Chen
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China
13th International Conference on Informatics in Control, Automation and Robotics, 2016

@inproceedings{lv2016opencl,

   title={OpenCL-accelerated Point Feature Histogram and Its Application in Railway Track Point Cloud Data Processing.},

   author={Lv, Dongxu and Wang, Peijun and Li, Wentao and Chen, Peng},

   booktitle={ICINCO (1)},

   pages={433–438},

   year={2016}

}

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To meet the requirements of railway track point cloud processing, an OpenCL-accelerated Point Feature Histogram method is proposed using heterogeneous computing to improve the low computation efficiency. According to the characteristics of parallel computing of OpenCL, the data structure for point cloud storage is reconfigured. With the kernel performance analysis by CodeXL, the data reading is improved and the load of ALU is promoted. In the test, it obtains 1.5 to 40 times speedup ratio compared with the original functions at same precision of CPU algorithm, and achieves better real-time performance and good compatibility to PCL.
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