Scattered point cloud simplification algorithm based on FPFH and FPS

Haipeng Li; Dan Xu; Yuting Fu; Yanan Liu; Jixiong Ma

doi:10.1117/12.2623150

16 February 2022 Scattered point cloud simplification algorithm based on FPFH and FPS

Haipeng Li, Dan Xu, Yuting Fu, Yanan Liu, Jixiong Ma

Proceedings Volume 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021); 120831F (2022) https://doi.org/10.1117/12.2623150
Event: Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 2021, Kunming, China

Abstract

3D point cloud simplification is an important pre-processing task in geometric reconstruction to save computer resources and increase reconstruction speed. Compared with traditional methods, the existing point cloud simplification algorithm based on k-means has a better effect on the extraction and retention of feature points, while there will be many larger holes near the feature points. In this paper, we propose a scattered point cloud simplification algorithm (SPSA). The SPSA strikes a balance between retaining enough feature points and keeping the sample points evenly distributed. The SPSA uses boundary search and the fast point feature histogram to extract feature points. Further, we apply the improved farthest point sampling algorithm to sample non-feature regions to ensure the integrity of the simplified model. Extensive experiment results on standardized information entropy evaluation show that the SPSA outperforms other simplification algorithms. In addition, the visualization results indicate that the proposed method can ensure the integrity of the simplified model and retain the most of feature information of the point cloud.

Citation Download Citation

Haipeng Li, Dan Xu, Yuting Fu, Yanan Liu, and Jixiong Ma "Scattered point cloud simplification algorithm based on FPFH and FPS", Proc. SPIE 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 120831F (16 February 2022); https://doi.org/10.1117/12.2623150

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