Acta Optica Sinica, Volume. 42, Issue 7, 0715001(2022)
Feature Segmentation Method of Aero-Engine Profile Point Cloud
[1] Li J J, Rui Z Y, Yan C F et al. Boundary extraction of defect hole of aero-engine blades based on double decision criteria[J]. Aeronautical Manufacturing Technology, 64, 55-62(2021).
[2] Zhang P C, Liu J, Yang H M et al. Laser overlapping three-dimensional reconstruction of damaged aero engine blade[J]. Laser & Optoelectronics Progress, 57, 161504(2020).
[3] Li Z W, Zhang P, Zhong K et al. Development and application of AutoScan series automated 3D measuring equipment for complex parts[J]. Acta Aeronautica et Astronautica Sinica, 42, 119-136(2021).
[4] Liu Y P, Chen L J, Li M et al. Segmentation method for point cloud of aeroengine pipelines[J]. Acta Aeronautica et Astronautica Sinica, 29, 285-291(2008).
[5] Guo Q D, Quan Y M. Depth image point cloud segmentation using spatial projection[J]. Acta Optica Sinica, 40, 1815001(2020).
[6] Rabbani T, van den Heuvel F, Vosselman G. Segmentation of point clouds using smoothness constraint[J]. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36, 248-253(2006).
[7] Lu M, Guo Y L, Zhang J et al. Recognizing objects in 3D point clouds with multi-scale local features[J]. Sensors, 14, 24156-24173(2014).
[8] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration[C]∥2009 IEEE International Conference on Robotics and Automation, May 12-17, 2009, Kobe, Japan., 3212-3217(2009).
[9] Wang X H, Wu L S, Chen H W et al. Feature line extraction from a point cloud based on region clustering segmentation[J]. Acta Optica Sinica, 38, 1110001(2018).
[10] Wang X H, Wu L S, Chen H W et al. Region segmentation of point cloud data based on improved particle swarm optimization fuzzy clustering[J]. Optics and Precision Engineering, 25, 563-573(2017).
[11] Vo A V, Truong-Hong L, Laefer D F et al. Octree-based region growing for point cloud segmentation[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 104, 88-100(2015).
[12] Ballard D H. Generalizing the Hough transform to detect arbitrary shapes[J]. Pattern Recognition, 13, 111-122(1981).
[13] Bolles R C, Fischler M A. A ransac-based approach to model fitting and its applications to finding cylinders in range data. [C]∥Proceedings of the 7th International Joint Conference on Artificial Intelligence, 637-643(1981).
[14] Vosselman G. Gorte B G H, Sithole G, et al. Recognising structure in laser scanner point clouds[J]. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 46, 33-38(2004).
[15] Wang W Q, Li Z C, Fu Y J et al. Multi-factor segmentation of point cloud based on improved multi-rule region growing[J]. Acta Optica Sinica, 41, 0528001(2021).
[16] Yang X S, Pan X F, Su S J et al. Data-driven awareness technology for space target image information[J]. Acta Optica Sinica, 41, 0315002(2021).
[17] Chai Y J, Ma J, Liu H. Deep graph attention convolution network for point cloud semantic segmentation[J]. Laser & Optoelectronics Progress, 58, 1210016(2021).
[18] Li H S, Wu Y J, Zheng Y P et al. A survey of 3D data analysis and understanding based on deep learning[J]. Chinese Journal of Computers, 43, 41-63(2020).
[19] Zhao L, Hu J, Liu H et al. Deep learning based on semantic segmentation for three-dimensional object detection from point clouds[J]. Chinese Journal of Lasers, 48, 1710004(2021).
[20] [20] MaturanaD, SchererS. VoxNet: a 3D convolutional neural network for real-time object recognition[C]∥2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 28-October 2, 2015, Hamburg, Germany. New York: IEEE Press, 2015: 922- 928.
[21] [21] Wu ZR, Song SR, KhoslaA, et al.3D ShapeNets: a deep representation for volumetric shapes[C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE Press, 2015: 1912- 1920.
[22] [22] Charles RQ, HaoS, Mo KC, et al.PointNet: deep learning on point sets for 3D classification and segmentation[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE Press, 2017: 77- 85.
[23] Qi C R, Yi L, Su H et al. -06-07)[2021-04-05]. https:∥arxiv., org/abs/1706, 02413(2017).
[24] Yi L, Kim V G, Ceylan D et al. A scalable active framework for region annotation in 3D shape collections[J]. ACM Transactions on Graphics, 35, 1-12(2016).
[25] Armeni I, Sener O, Zamir A R et al. 3D semantic parsing of large-scale indoor spaces[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA., 1534-1543(2016).
[26] Shen Y R, Feng C, Yang Y Q et al. -12-19)[2021-04-05]. https:∥arxiv.org/abs/1712.06760v1.(2017).
[27] Guerrero P, Kleiman Y, Ovsjanikov M et al. PCPNet learning local shape properties from raw point clouds[J]. Computer Graphics Forum, 37, 75-85(2018).
[28] Rakotosaona M J, la Barbera V, Guerrero P et al. PointCleanNet: learning to denoise and remove outliers from dense point clouds[J]. Computer Graphics Forum, 39, 185-203(2020).
[29] Gu S T, Wang L, Ma Y X et al. Local feature description of LiDAR point cloud data based on hierarchical Mercator projection[J]. Acta Optica Sinica, 40, 2015001(2020).
[30] Wang Y, Sun Y B, Liu Z W et al. Dynamic graph CNN for learning on point clouds[J]. ACM Transactions on Graphics, 38, 1-12(2019).
[31] Kaick O V, Fish N, Kleiman Y et al. Shape segmentation by approximate convexity analysis[J]. ACM Transactions on Graphics, 34, 1-11(2014).
Get Citation
Copy Citation Text
Jieqiong Yan, Laishui Zhou, Shaoqian Hu, Siyang Wen. Feature Segmentation Method of Aero-Engine Profile Point Cloud[J]. Acta Optica Sinica, 2022, 42(7): 0715001
Category: Machine Vision
Received: Jul. 9, 2021
Accepted: Sep. 27, 2021
Published Online: Mar. 28, 2022
The Author Email: Zhou Laishui (zlsme@nuaa.edu.cn)