article · Research Journal of Applied Sciences Engineering and Technology · 2013

Local Optimum Triangulation for Unorganized Points Cloud

Nan Wang, Qiang Zhang, Donghent Zhou, Xiaopeng Wei

Cited by 0Open access

Abstract

The triangulation of the unorganized data from the 3D scanner is always an important research subject of the CAD, computer geometry, reverse engineering and other areas. This paper introduces the current mainstream methods of triangulation that based on 3D points cloud data: plane projection method and direct method of division. This paper put forward a local optimization of direct triangulations method.

Cite this paper

APA 7

Wang, N., Zhang, Q., Zhou, D., & Wei, X. (2013). Local Optimum Triangulation for Unorganized Points Cloud. Research Journal of Applied Sciences Engineering and Technology, 6(10), 1862–1867. https://doi.org/10.19026/rjaset.6.3916

MLA 9

Wang, Nan, et al. “Local Optimum Triangulation for Unorganized Points Cloud.” Research Journal of Applied Sciences Engineering and Technology, vol. 6, no. 10, 2013, pp. 1862–67, https://doi.org/10.19026/rjaset.6.3916.

Chicago

Wang, Nan, Qiang Zhang, Donghent Zhou, and Xiaopeng Wei. 2013. “Local Optimum Triangulation for Unorganized Points Cloud.” Research Journal of Applied Sciences Engineering and Technology 6 (10): 1862–67. https://doi.org/10.19026/rjaset.6.3916.

Harvard

Wang, N. et al. (2013) ‘Local Optimum Triangulation for Unorganized Points Cloud’, Research Journal of Applied Sciences Engineering and Technology, 6(10), pp. 1862–1867. Available at: https://doi.org/10.19026/rjaset.6.3916.

BibTeX

@article{wang2013local,
  title = {{Local Optimum Triangulation for Unorganized Points Cloud}},
  author = {Wang, Nan and Zhang, Qiang and Zhou, Donghent and Wei, Xiaopeng},
  journal = {Research Journal of Applied Sciences Engineering and Technology},
  volume = {6},
  number = {10},
  pages = {1862--1867},
  year = {2013},
  doi = {10.19026/rjaset.6.3916}
}

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