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
- Chinese Journal of Lasers
- Vol. 46, Issue 4, 0404009 (2019)
Fig. 1. Schematic of spatial dynamic grid Q
Fig. 2. Schematic of projection of Pi and k neighbor points onto their micro-cut plane
Fig. 3. Local two-dimensional coordinate system established in 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. 5. Using vector deflection angle to select next connection point
Fig. 6. Problems during vector deflection angle sorting. (a) Question 1; (b) question 2
Fig. 7. Schematic of traditional cubic B-spline algorithm
Fig. 8. Schematic of improved cubic B-spline algorithm
Fig. 9. Fitting connection comparison by three methods. (a) Circle; (b) sinusoid
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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Table 1. Extraction status of feature points and running time under different parameters
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Table 2. Extraction status of feature points and running time by two algorithms
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Table 3. Deviations between randomly selected 40 points and boundary lines
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