• Acta Optica Sinica
  • Vol. 37, Issue 11, 1115007 (2017)
Siyong Fu*, Lushen Wu, and Huawei Chen
Author Affiliations
  • School of Mechanical and Electrical Engineering, Nanchang University, Nanchang, Jiangxi 330031, China
  • show less
    DOI: 10.3788/AOS201737.1115007 Cite this Article Set citation alerts
    Siyong Fu, Lushen Wu, Huawei Chen. Point Cloud Simplification Method Based on Space Grid Dynamic Partitioning[J]. Acta Optica Sinica, 2017, 37(11): 1115007 Copy Citation Text show less
    References

    [1] Yuan Xiaocui, Wu Lushen, Chen Huawei. Feature preserving point cloud simplification[J]. Optics and Precision Engineering, 23, 2666-2676(2015).

    [2] Chen Zhangwen, Da Feipeng. 3D point cloud simplification algorithm based on fuzzy entropy iteration[J]. Acta Optica Sinica, 33, 0815001(2013).

    [3] Yao Wanqiang, Zheng Junliang, Chen Peng et al. An octree-based mesh simplification algorithms for 3-dimension cloud data[J]. Science of Surveying and Mapping, 41, 18-22(2016).

    [4] Martin R R, Stroud I A, Marshall A D. Data reduction for reverse engineering[C]. Proceedings of the 7th conference on Information Geometers, Limited, 85-100(1997).

    [5] Lee K H, Woo H, Suk T. Point data reduction using 3D grids[J]. The International Journal of Advanced Manufacturing Technology, 18, 201-210(2001). http://link.springer.com/article/10.1007/s001700170075

    [6] Chen Y H, Ng C T, Wang Y Z. Data reduction in integrated reverse engineering and rapid prototyping[J]. International Journal of Computer Integrated Manufacturing, 12, 97-103(1999). http://www.tandfonline.com/doi/abs/10.1080/095119299130344

    [7] Pauly M, Gross M, Kobbelt L P. Efficient simplification of point-sampled surfaces[C]. Proceedings of the IEEE Conference on Visualization, 163-170(2002).

    [8] Weir D J, Milroy M J, Bradley C et al. Reverse engineering physical models employing wrap-around B-spline surfaces and quadrics[J]. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture, 210, 147-157(1996). http://www.researchgate.net/publication/245385611_Reverse_engineering_physical_models_employing_wraparound_Bspline_surfaces_and_quadrics

    [9] Zhou Yu, Zhang Wanbing, Du Farong et al. Algorithm for reduction of scattered point cloud data based on curvature[J]. Transactions of Beijing Institute of Technology, 30, 785-789(2010).

    [10] Zhang Yuhe, Geng Guohua, Wei Xiaoran et al. Point clouds simplification with geometric feature reservation[J]. Journal of Computer-Aided Design and Computer Graphics, 28, 1420-1427(2016).

    [11] Liu Ying, Wang Chaoyang, Gao Nan et al. Point cloud adaptive simplification of feature extraction[J]. Optics and Precision Engineering, 25, 245-254(2017).

    [12] Han H, Han X, Sun F et al. Point cloud simplification with preserved edge based on normal vector[J]. Optik-International Journal for Light and Electron Optics, 126, 2157-2162(2015). http://www.sciencedirect.com/science/article/pii/S0030402615004052

    [13] Wang Lihui, Yuan Baozong. Feature point detection for 3D scattered point cloud model[J]. Sigal Processing, 27, 932-938(2011).

    [14] Chen Y, Yue L. A method for dynamic simplification of massive point cloud[C]. IEEE International Conference on Industrial Technology (ICIT), 1690-1693(2016).

    [15] Zhu Yu, Kang Baosheng, Li Honganet al. Improved algorithm for point cloud data simplification[J]. 32(2): 521-523+544(2012).

    [16] Lee P F, Huang C P. The DSO feature based point cloud simplification[C]. IEEE Eighth International Conference on Computer Graphics, Imaging and Visualization, 1-6(2011).

    [17] Schnabel R, Klein R. Octree-based point-cloud compression[C]. Eurographics/IEEE Vgtc Conference on Point-Based Graphics, 111-121(2006).

    [18] Huang M, Yang F, Zhang J et al[J]. Point cloud data simplification using movable mesh generation Metallurgical & Mining Industry, 2015, 230-237.

    [19] Zhu Junfeng, Hu Xiangyun, Zhang Zuxun et al. Hierarchical outlier detection for point cloud data using a density analysis method[J]. Acta Geodaetica et Cartographica Sinica, 44, 282-291(2015).

    [20] Lei Yuzhen, Li Zhongwei, Zhong Kai et al. Mismatching marked points correction method based on random sample consensus algorithm[J]. Acta Optica Sinica, 33, 0315002(2013).

    [21] Chen Long, Cai Yong, Zhang Jiansheng et al. Feature point extraction of scattered point cloud based on multiple parameters hybridization method[J]. Application Research of Computers, 34, 2867-2870(2017).

    [22] Zhang Y, Geng G, Wei X et al. A statistical approach for extraction of feature lines from point clouds[J]. Computers & Graphics, 56, 31-45(2016). http://dl.acm.org/citation.cfm?id=2933031

    [23] Shi B Q, Liang J, Liu Q. Adaptive simplification of point cloud using k-means clustering[J]. Computer-Aided Design, 43, 910-922(2011).

    CLP Journals

    [1] Yunlong Su, Xueliang Ping. Point Cloud Edge-Extraction Algorithm Based on Gaussian Map Clustering[J]. Laser & Optoelectronics Progress, 2019, 56(11): 111506

    [2] Bowen Deng, Zhaoba Wang, Yong Jin, Youxing Chen, Qizhou Wu, Haiyang Li. Feature Extraction Method of Laser Scanning Point Cloud Based on Morphological Gradient[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051203

    [3] Yunlong Su, Xueliang Ping. Point Cloud Edge-Extraction Algorithm Based on Gaussian Map Clustering[J]. Laser & Optoelectronics Progress, 2019, 56(11): 111506

    Siyong Fu, Lushen Wu, Huawei Chen. Point Cloud Simplification Method Based on Space Grid Dynamic Partitioning[J]. Acta Optica Sinica, 2017, 37(11): 1115007
    Download Citation