Globally consistent registration of terrestrial laser scans via graph optimization

[1]  R. Prim Shortest connection networks and some generalizations , 1957 .

[2]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[3]  Daniel P. Huttenlocher,et al.  Fast affine point matching: an output-sensitive method , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Gérard G. Medioni,et al.  Object modelling by registration of multiple range images , 1992, Image Vis. Comput..

[5]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Naokazu Yokoya,et al.  A Robust Method for Registration and Segmentation of Multiple Range Images , 1995, Comput. Vis. Image Underst..

[7]  Robert Bergevin,et al.  Towards a General Multi-View Registration Technique , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Evangelos E. Milios,et al.  Globally Consistent Range Scan Alignment for Environment Mapping , 1997, Auton. Robots.

[9]  Peter Johannes Neugebauer,et al.  Reconstruction of Real-World Objects via Simultaneous Registration and Robust Combination of Multiple Range Images , 1997, Int. J. Shape Model..

[10]  Francis Schmitt,et al.  A Solution for the Registration of Multiple 3D Point Sets Using Unit Quaternions , 1998, ECCV.

[11]  Kari Pulli,et al.  Multiview registration for large data sets , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[12]  Andrew E. Johnson,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Andrew Zisserman,et al.  MLESAC: A New Robust Estimator with Application to Estimating Image Geometry , 2000, Comput. Vis. Image Underst..

[14]  Brendan J. Frey,et al.  Factor graphs and the sum-product algorithm , 2001, IEEE Trans. Inf. Theory.

[15]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  M. Devrim Mehmet Devrim Akça FULL AUTOMATIC REGISTRATION OF LASER SCANNER POINT CLOUDS , 2003 .

[17]  Martial Hebert,et al.  Fully automatic registration of multiple 3D data sets , 2003, Image Vis. Comput..

[18]  Kwang-Ho Bae Automated Registration of Unorganised Point Clouds from Terrestrial Laser Scanners , 2004 .

[19]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[20]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[21]  Kostas Daniilidis,et al.  Fully Automatic Registration of 3D Point Clouds , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[22]  Florent Lamiraux,et al.  Metric-based iterative closest point scan matching for sensor displacement estimation , 2006, IEEE Transactions on Robotics.

[23]  Claus Brenner,et al.  Registration of terrestrial laser scanning data using planar patches and image data , 2006 .

[24]  Anton van den Hengel,et al.  Thrift: Local 3D Structure Recognition , 2007, 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007).

[25]  George Vosselman,et al.  An integrated approach for modelling and global registration of point clouds , 2007 .

[26]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[27]  Susanne Becker,et al.  Automatic Marker-Free Registration of Terrestrial Laser Scans using Reflectance Features , 2007 .

[28]  Bobby Bodenheimer,et al.  Synthesis and evaluation of linear motion transitions , 2008, TOGS.

[29]  N. Mitra,et al.  4-points congruent sets for robust pairwise surface registration , 2008, SIGGRAPH 2008.

[30]  Carsten Rother,et al.  FusionFlow: Discrete-continuous optimization for optical flow estimation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[31]  Claus Brenner,et al.  Coarse orientation of terrestrial laser scans in urban environments , 2008 .

[32]  Nico Blodow,et al.  Aligning point cloud views using persistent feature histograms , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[33]  Joachim Hertzberg,et al.  Globally consistent 3D mapping with scan matching , 2008, Robotics Auton. Syst..

[34]  S. Filin,et al.  Keypoint based autonomous registration of terrestrial laser point-clouds , 2008 .

[35]  Vladimir Pekar,et al.  Full orientation invariance and improved feature selectivity of 3D SIFT with application to medical image analysis , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[36]  Nico Blodow,et al.  Fast Point Feature Histograms (FPFH) for 3D registration , 2009, 2009 IEEE International Conference on Robotics and Automation.

[37]  Sisi Zlatanova,et al.  Automatic Registration of Terrestrial Laser Scanning Point Clouds using Panoramic Reflectance Images , 2009, Sensors.

[38]  Geraldine S. Cheok,et al.  Fast automatic registration of range images from 3D imaging systems using sphere targets , 2009 .

[39]  Najla Megherbi Bouallagu,et al.  Object Recognition using 3D SIFT in Complex CT Volumes , 2010, BMVC.

[40]  Benjamin Bustos,et al.  Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes , 2011, The Visual Computer.

[41]  Radu Bogdan Rusu,et al.  3D is here: Point Cloud Library (PCL) , 2011, 2011 IEEE International Conference on Robotics and Automation.

[42]  Ullrich Köthe,et al.  The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models , 2012, ECCV.

[43]  Federico Tombari,et al.  Performance Evaluation of 3D Keypoint Detectors , 2012, International Journal of Computer Vision.

[44]  Jörg H. Kappes,et al.  OpenGM: A C++ Library for Discrete Graphical Models , 2012, ArXiv.

[45]  Konrad Schindler,et al.  AUTOMATIC REGISTRATION OF TERRESTRIAL LASER SCANNER POINT CLOUDS USING NATURAL PLANAR SURFACES , 2012 .

[46]  Konrad Schindler,et al.  Approximate registration of point clouds with large scale differences , 2013 .

[47]  Andrea Tagliasacchi,et al.  Sparse Iterative Closest Point , 2013, Comput. Graph. Forum.

[48]  Jiaolong Yang,et al.  Go-ICP: Solving 3D Registration Efficiently and Globally Optimally , 2013, 2013 IEEE International Conference on Computer Vision.

[49]  Konrad Schindler,et al.  Detection- and Trajectory-Level Exclusion in Multiple Object Tracking , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[50]  Marc Pollefeys,et al.  Automatic Registration of RGB-D Scans via Salient Directions , 2013, 2013 IEEE International Conference on Computer Vision.

[51]  Olaf Hellwich,et al.  Comparison of 3D interest point detectors and descriptors for point cloud fusion , 2014, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

[52]  Jun Xiao,et al.  An Initial Registration Method of Point Clouds Based on Random Sampling , 2014 .

[53]  Konrad Schindler,et al.  Keypoint-based 4-Points Congruent Sets – Automated marker-less registration of laser scans , 2014 .

[54]  Konrad Schindler,et al.  Fast registration of laser scans with 4-point congruent sets - what works and what doesn't , 2014 .

[55]  Olaf Hellwich,et al.  Automatic registration of unordered point clouds acquired by Kinect sensors using an overlap heuristic , 2015 .