Chinese Journal of Lasers, Volume. 46, Issue 4, 0404009(2019)
Point Cloud Feature Regularization Based on Fusion of Improved Field Force and Judging Criterion
Fig. 2. Schematic of projection of Pi and k neighbor points onto their micro-cut plane
Fig. 4. Unitized projection vector. (a) Neighborhood points tilted to one side (boundary feature point); (b) neighborhood points distributed evenly (internal point)
Fig. 6. Problems during vector deflection angle sorting. (a) Question 1; (b) question 2
Fig. 10. Partial extraction effect diagrams under different parameters. (a) k=30, ε=0.48; (b) k=30, ε=0.52; (c) k=28, ε=0.50; (d) k=30, ε=0.50
Fig. 11. Feature extraction comparison and fitting of point cloud model. (a)(f)(k) Original point clouds; (b)(g)(l) algorithmin Ref. [11]; (c)(h)(m) algorithm in Ref. [12]; (d)(i)(n) proposed algorithm; (e)(j)(o) feature regularization
Fig. 12. Feature extraction and fitting of Yangtze River Erqi Bridge. (a) Side view; (e) main view; (i) top view; (b)(f)(j) algorithm in Ref. [12]; (c)(g)(k) proposed algorithm; (d)(h)(l) feature regularization
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Qing Liu, Guang Zhang, Xijiang Chen. Point Cloud Feature Regularization Based on Fusion of Improved Field Force and Judging Criterion[J]. Chinese Journal of Lasers, 2019, 46(4): 0404009
Category: measurement and metrology
Received: Oct. 22, 2018
Accepted: Jan. 14, 2019
Published Online: May. 9, 2019
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