persistent feature histograms. In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3384-3391. IEEE, 2008 [10] Yangyan Li, Soeren Pirk, Hao Su, Charles R Qi, and Leonidas J Guibas. Fpnn: Field probing neural networks for 3d data. ar Xiv preprint ar Xiv: 1605.06240, 2016 [11]M. Tatarchenko, A. Dosovitskiy, and T. Brox Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs In IEEE International Conference on Computer Vision(ICCV), 2017 [12]. Song and J. Xiao. Deep sliding shapes for amodal 3d object detection in rgb-d images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 808 816.2016 [13]QiCR, Liu W, Wu C, et al. Frustum pointnets for 3d object detection from rgb-d data[ C]/Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018 918-927 [14]Jiang M, Wu Y, Lu C. Pointsift: A sift-like network module for 3d point cloud semantic segmentation[J]- ar Xiv preprint arXiv: 1807.00652, 2018 [15 Lin M, Chen Q, Yan S Network in network[J]. arXiv preprint arXiv: 1312. 4400, 2013 [16]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(TOG), 2016, 35(6): 210 作者简介 刘旭辉,北京航空航天大学电子信息工程学院,北京航空航天大学医工交叉创新研究院 邮箱:1332671326@qq.com 王宏燕,西安卫星测控中心,邮箱:155190708@qq.com (c)1994-2019ChinaAcademicJournalElectronicpUblishingHouse.Allrightsreservedhttp://www.cnki.netpersistent feature histograms. In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3384–3391. IEEE, 2008. [10] Yangyan Li, Soeren Pirk, Hao Su, Charles R Qi, and Leonidas J Guibas. Fpnn: Field probing neural networks for 3d data. arXiv preprint arXiv:1605.06240, 2016. [11] M. Tatarchenko, A. Dosovitskiy, and T. Brox. Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs. In IEEE International Conference on Computer Vision (ICCV), 2017. [12] S. Song and J. Xiao. Deep sliding shapes for amodal 3d object detection in rgb-d images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 808– 816, 2016. [13] Qi C R, Liu W, Wu C, et al. Frustum pointnets for 3d object detection from rgb-d data[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018: 918-927. [14] Jiang M, Wu Y, Lu C. Pointsift: A sift-like network module for 3d point cloud semantic segmentation[J]. arXiv preprint arXiv:1807.00652, 2018. [15] Lin M, Chen Q, Yan S. Network in network[J]. arXiv preprint arXiv:1312.4400, 2013. [16] 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 (TOG), 2016, 35(6): 210. 作者简介： 刘旭辉，北京航空航天大学电子信息工程学院，北京航空航天大学医工交叉创新研究院， 邮箱：1332671326@qq.com； 王宏燕，西安卫星测控中心，邮箱:155190708@qq.com