Innovations for Shape Analysis,
Models and Algorithms
Point cloud segmentation and denoising via constrained least squares normal estimates
Publication
, Chapter
Zhao, H; Castillo, E; Liang, J
2013
Duke Scholars
Citation
APA
Chicago
ICMJE
MLA
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Zhao, H., Castillo, E., & Liang, J. (2013). Point cloud segmentation and denoising via constrained least squares normal estimates. In M. Breuß, A. Bruckstein, & P. Maragos (Eds.), Innovations for Shape Analysis,Models and Algorithms (pp. 283–299). Springer. https://doi.org/10.1007/978-3-642-34141-0
Zhao, Hongkai, Edward Castillo, and Jian Liang. “Point cloud segmentation and denoising via constrained least squares normal estimates.” In Innovations for Shape Analysis,Models and Algorithms, edited by Michael Breuß, Alfred Bruckstein, and Petros Maragos, 283–99. Springer, 2013. https://doi.org/10.1007/978-3-642-34141-0.
Zhao H, Castillo E, Liang J. Point cloud segmentation and denoising via constrained least squares normal estimates. In: Breuß M, Bruckstein A, Maragos P, editors. Innovations for Shape Analysis,Models and Algorithms. Springer; 2013. p. 283–99.
Zhao, Hongkai, et al. “Point cloud segmentation and denoising via constrained least squares normal estimates.” Innovations for Shape Analysis,Models and Algorithms, edited by Michael Breuß et al., Springer, 2013, pp. 283–99. Manual, doi:10.1007/978-3-642-34141-0.
Zhao H, Castillo E, Liang J. Point cloud segmentation and denoising via constrained least squares normal estimates. In: Breuß M, Bruckstein A, Maragos P, editors. Innovations for Shape Analysis,Models and Algorithms. Springer; 2013. p. 283–299.