[1] WU B,XIE L,HU H,et al.Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2018(139):119-132. [2] NEX F,GERKE M,REMONDINO F,et al.ISPRS benchmark for multi-platform photogrammetry[C]//Proceedings of 2015 ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Munich:ISPRS,2015:135-142. [3] GAO X,SHEN S,ZHOU Y,et al.Ancient Chinese architecture 3D preservation by merging ground and aerial point clouds[J].ISPRS Journal of Photogrammetry and Remote Sensing,2018(143):72-84. [4] LOWE D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision,2004,60(2):91-110. [5] BAY H,ESS A,TUYTELAARS T,et al. Speeded-up robust features (SURF)[J]. Computer Vision and Image Understanding,2008,110(3):346-359. [6] SHAH R,DESHPANDE A,NARAYANAN P J. Multistage SFM:revisiting incremental structure from motion[C]//Proceedings of 2014 International Conference on 3D Vision. Tokyo:IEEE,2014:417-424. [7] NODA M,TOMOKAZU T. Vehicle ego-localization by matching in-vehicle camera images to an aerial image[C]//Proceedings of 2010 Asian Conference on Computer Vision 2010 Workshops. Queenstown:Springer,2010:163-173. [8] JENDE P,NEX F,GERKE M,et al. A fully automatic approach to register mobile mapping and airborne imagery to support the correction of platform trajectories in GNSS-denied urban areas[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2018,141:86-99. [9] WOLFF M,COLLINS R T,LIU Y X. Regularity-driven building facade matching between aerial and street views[C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Seattle:IEEE,2016:1591-1600. [10] TIAN Y C,CHEN C,SHAH M. Cross-view image matching for geo-localization in urban environments[C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. Honolulu:IEEE,2017:1998-2006. [11] LIN T Y,CUI Y,BELONGIE S,et al. Learning deep representations for ground-to-aerial geolocalization[C]//Proceedings of 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston:IEEE,2015:5007-5015. [12] 杨璐宏,吴玮,王芮.基于空地影像联合的精细化三维重建研究[J].测绘通报,2021(S1):144-148. [13] 赵文更,张旭,邵晴晴.融合反射强度图像的地铁隧道点云自动配准[J].测绘通报,2020(9):38-41. [14] 马伟丽,王健,孙文潇.曲率约束的激光点云全局优化配准算法[J].遥感信息,2019,34(4):62-67. [15] BESL P J,MCKAY N D. Method for registration of 3D shapes[C]//Proceedings of 1992 Sensor Fusion IV:Control Paradigms and Data Structures.[S.l.]:International Society for Optics and Photonics,1992. [16] CHETVERIKOV D,SVIRKO D,STEPANOV D,et al. The trimmed iterative closest point algorithm[C]//Proceedings of 2002 IEEE International Conference on Pattern Recognition. Quebec:IEEE,2002. [17] YU Z. Intrinsic shape signatures:a shape descriptor for 3D object recognition[C]//Proceedings of 2009 IEEE International Conference on Computer Vision Workshops. Kyoto:IEEE,2009:689-696. [18] FROME A,HUBER D,KOLLURI R,et al. Recognizing objects in range data using regional point descriptors[C]//Proceedings of the 8th European Conference on Computer Vision. Prague:Springer,2004:224-237. [19] RUSU R B,BLODOW N,BEETZ M. Fast point feature histograms (FPFH) for 3D registration[C]//Proceedings of 2009 IEEE International Conference on Robotics&Automation. Kobe:IEEE,2009. [20] 李仁忠,杨曼,田瑜,等.基于ISS特征点结合改进ICP的点云配准算法[J].激光与光电子学进展,2017,54(11):312-319. |