Recent developments and trends in point set registration methods

The problem of registering point sets has been formulated.Recent developments and trends in point set registration (PSR) methods have been extensively discussed.Limitations of PSR methods have been exposed and some possible solutions recommended.Performance evaluation framework for PSR methods has been established.Challenging issues to evaluate PSR algorithms have been discussed. Point set registration (PSR) is the process of computing a spatial transformation that optimally aligns pairs of point sets. The method helps to amalgamate multiple datasets into a common coordinate system. Because of their immense practical applications, several studies have attempted to address challenges inherent in the PSR problem. However, limited works exist to discuss recent developments, failures, and trends of the PSR methods. To date, a classical work of Tam et al., published in 2013, can be regarded as a comprehensive review paper for registration methods. Nevertheless, this work has inadequately revealed a range of possible knowledge gaps of the previous studies. Additionally, since the publication year of their work, more superior and state-of-the-art methods have been proposed. The present study surveys PSR approaches until 2017, and our primary focus is to expose central ideas and limitations of the methods to facilitate experts and practitioners advance the field.

[1]  Marc Rioux,et al.  Three-dimensional registration using range and intensity information , 1994, Other Conferences.

[2]  Baba C. Vemuri,et al.  Robust Point Set Registration Using Gaussian Mixture Models , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[4]  Nico Blodow,et al.  Towards 3D Point cloud based object maps for household environments , 2008, Robotics Auton. Syst..

[5]  Vladimir Petrovic,et al.  Non-Rigid Registration Assessment Without Ground Truth , 2006 .

[6]  Steven Lake Waslander,et al.  Multi-Channel Generalized-ICP: A robust framework for multi-channel scan registration , 2017, Robotics Auton. Syst..

[7]  Sebastian Thrun,et al.  Real time motion capture using a single time-of-flight camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Zbigniew Michalewicz,et al.  Analysis of Stability, Local Convergence, and Transformation Sensitivity of a Variant of the Particle Swarm Optimization Algorithm , 2016, IEEE Transactions on Evolutionary Computation.

[9]  Miguel Á. Carreira-Perpiñán,et al.  Non-rigid point set registration: Coherent Point Drift , 2006, NIPS.

[10]  Sang Wook Lee,et al.  ICP Registration Using Invariant Features , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Zhengyou Zhang,et al.  Iterative point matching for registration of free-form curves and surfaces , 1994, International Journal of Computer Vision.

[12]  Leonidas J. Guibas,et al.  Non-Rigid Registration Under Isometric Deformations , 2008 .

[13]  S. Gold Matching and learning structural and spatial representations with neural networks , 1996 .

[14]  Jie Yang,et al.  A robust coherent point drift approach based on rotation invariant shape context , 2017, Neurocomputing.

[15]  Nicolas David,et al.  IMPROVING 3D LIDAR POINT CLOUD REGISTRATION USING OPTIMAL NEIGHBORHOOD KNOWLEDGE , 2012 .

[16]  Zhuowen Tu,et al.  Robust Point Matching via Vector Field Consensus , 2014, IEEE Transactions on Image Processing.

[17]  Roland Siegwart,et al.  Challenging data sets for point cloud registration algorithms , 2012, Int. J. Robotics Res..

[18]  Yunwen Xu,et al.  Aggregation of Graph Models and Markov Chains by Deterministic Annealing , 2014, IEEE Transactions on Automatic Control.

[19]  Georgios Papaioannou,et al.  Efficient Sparse ICP , 2015, Comput. Aided Geom. Des..

[20]  Marc Levoy,et al.  Zippered polygon meshes from range images , 1994, SIGGRAPH.

[21]  D. Hill,et al.  Registration of MR and CT images for skull base surgery using point-like anatomical features. , 1991, The British journal of radiology.

[22]  Mark Pauly,et al.  Example-based facial rigging , 2010, SIGGRAPH 2010.

[23]  Ping Wang,et al.  A refined coherent point drift (CPD) algorithm for point set registration , 2011, Science China Information Sciences.

[24]  Darius Burschka,et al.  Stochastic Optimization for Rigid Point Set Registration , 2009, ISVC.

[25]  Gang Wang,et al.  Context-Aware Gaussian Fields for Non-rigid Point Set Registration , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  Ruigang Yang,et al.  Accurate 3D pose estimation from a single depth image , 2011, 2011 International Conference on Computer Vision.

[27]  Yücel Yemez,et al.  Minimum-Distortion Isometric Shape Correspondence Using EM Algorithm , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Yuehaw Khoo,et al.  Non-Iterative Rigid 2D/3D Point-Set Registration Using Semidefinite Programming , 2015, IEEE Transactions on Image Processing.

[29]  Zhiguo Cao,et al.  A fast and robust local descriptor for 3D point cloud registration , 2016, Inf. Sci..

[30]  James E. Fowler,et al.  Hyperspectral Image Classification Using Gaussian Mixture Models and Markov Random Fields , 2014, IEEE Geoscience and Remote Sensing Letters.

[31]  Zhuowen Tu,et al.  Robust Estimation of Nonrigid Transformation for Point Set Registration , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[32]  Darius Burschka,et al.  Stochastic global optimization for robust point set registration , 2011, Comput. Vis. Image Underst..

[33]  Jian Zhao,et al.  A 3D pointcloud registration algorithm based on fast coherent point drift , 2014, 2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).

[34]  Chia-Ling Tsai,et al.  Registration of Challenging Image Pairs: Initialization, Estimation, and Decision , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Kenneth Rose,et al.  Deterministic Annealing-Based Optimization for Zero-Delay Source-Channel Coding in Networks , 2015, IEEE Transactions on Communications.

[36]  Steven Gold,et al.  A Framework for Non-rigid Matching and Correspondence , 1995, NIPS.

[37]  Kai Zhang,et al.  A Robust Point-Matching Algorithm for Remote Sensing Image Registration , 2014, IEEE Geoscience and Remote Sensing Letters.

[38]  Purang Abolmaesumi,et al.  Group-Wise Registration of Point Sets for Statistical Shape Models , 2012, IEEE Transactions on Medical Imaging.

[39]  Zhiyong Zhou,et al.  Direct point-based registration for precise non-rigid surface matching using Student's-t mixture model , 2017, Biomed. Signal Process. Control..

[40]  Q. M. Jonathan Wu,et al.  Multiple Kernel Point Set Registration , 2016, IEEE Transactions on Medical Imaging.

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

[42]  Guillermo Sapiro,et al.  Video Compressive Sensing Using Gaussian Mixture Models , 2014, IEEE Transactions on Image Processing.

[43]  Andrea Torsello,et al.  Sampling Relevant Points for Surface Registration , 2011, 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission.

[44]  Martial Hebert,et al.  Scale selection for classification of point-sampled 3D surfaces , 2005, Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05).

[45]  Marc Levoy,et al.  Fitting smooth surfaces to dense polygon meshes , 1996, SIGGRAPH.

[46]  Miin-Shen Yang,et al.  A robust EM clustering algorithm for Gaussian mixture models , 2012, Pattern Recognit..

[47]  Pradeep Buddharaju,et al.  Physiology-Based Face Recognition in the Thermal Infrared Spectrum , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[48]  Li Shan,et al.  Stability and Convergence Analysis of a Decoupled Algorithm for a Fluid-Fluid Interaction Problem , 2016, SIAM J. Numer. Anal..

[49]  Wesley E. Snyder,et al.  Optimization of functions with many minima , 1991, IEEE Trans. Syst. Man Cybern..

[50]  Walter G. Kropatsch,et al.  Graph-based point drift: Graph centrality on the registration of point-sets , 2015, Pattern Recognit..

[51]  Narendra Ahuja,et al.  Robust Registration and Tracking Using Kernel Density Correlation , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[52]  Jianmin Dong,et al.  Improvement of affine iterative closest point algorithm for partial registration , 2017, IET Comput. Vis..

[53]  Hock Woon Hon,et al.  An Automatic Robust Image Registration Algorithm for Aerial Mapping , 2015, Int. J. Image Graph..

[54]  Yongdong Zhang,et al.  Parallel deblocking filter for HEVC on many-core processor , 2014 .

[55]  Jiayi Ma,et al.  A Mixture Model for Robust Point Matching under Multi-Layer Motion , 2014, PloS one.

[56]  Sven Kabus,et al.  B-spline registration of 3D images with Levenberg-Marquardt optimization , 2004, SPIE Medical Imaging.

[57]  Roland Siegwart,et al.  Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration , 2012 .

[58]  Jian Zhao,et al.  Accelerated Coherent Point Drift for Automatic Three-Dimensional Point Cloud Registration , 2016, IEEE Geoscience and Remote Sensing Letters.

[59]  Dinggang Shen,et al.  S‐HAMMER: Hierarchical attribute‐guided, symmetric diffeomorphic registration for MR brain images , 2014, Human brain mapping.

[60]  Nanning Zheng,et al.  Scaling iterative closest point algorithm for registration of m-D point sets , 2010, J. Vis. Commun. Image Represent..

[61]  Nanning Zheng,et al.  Affine iterative closest point algorithm for point set registration , 2010, Pattern Recognit. Lett..

[62]  Qianjin Feng,et al.  Coherent Point Drift Registration Combined with Image Feature and its Application , 2013 .

[63]  Takeo Kanade,et al.  A Correlation-Based Approach to Robust Point Set Registration , 2004, ECCV.

[64]  Lixing Han,et al.  Implementing the Nelder-Mead simplex algorithm with adaptive parameters , 2010, Computational Optimization and Applications.

[65]  Roland Siegwart,et al.  A Review of Point Cloud Registration Algorithms for Mobile Robotics , 2015, Found. Trends Robotics.

[66]  Marc Levoy,et al.  A volumetric method for building complex models from range images , 1996, SIGGRAPH.

[67]  Lei Zhang,et al.  An Efficient Globally Optimal Algorithm for Asymmetric Point Matching , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[68]  Juta Pichitlamken,et al.  Nelder–Mead Method with Local Selection Using Memory for Discrete Stochastic Optimization , 2016 .

[69]  Marc Levoy,et al.  Efficient variants of the ICP algorithm , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.

[70]  Hans-Peter Seidel,et al.  Robust filtering of noisy scattered point data , 2005, Proceedings Eurographics/IEEE VGTC Symposium Point-Based Graphics, 2005..

[71]  Dong-Soo Kwon,et al.  GMM-based 3D object representation and robust tracking in unconstructed dynamic environments , 2013, 2013 IEEE International Conference on Robotics and Automation.

[72]  Michael J. Black,et al.  Home 3D body scans from noisy image and range data , 2011, 2011 International Conference on Computer Vision.

[73]  Zhuowen Tu,et al.  Robust $L_{2}E$ Estimation of Transformation for Non-Rigid Registration , 2015, IEEE Transactions on Signal Processing.

[74]  Greg Stortz,et al.  An algorithm for automatic crystal identification in pixelated scintillation detectors using thin plate splines and Gaussian mixture models , 2016, Physics in medicine and biology.

[75]  Adam Chromy,et al.  A Study on Performace of Levenberg-Marquardt and CMA-ES Optimization Methods for Atlas-based 2D/3D Reconstruction , 2016 .

[76]  Eric Mjolsness Bayesian Inference on Visual Grammars by Neural Nets that Optimize , 2004 .

[77]  Zbigniew Michalewicz,et al.  Stability Analysis of the Particle Swarm Optimization Without Stagnation Assumption , 2016, IEEE Transactions on Evolutionary Computation.

[78]  Lena Maier-Hein,et al.  Convergent Iterative Closest-Point Algorithm to Accomodate Anisotropic and Inhomogenous Localization Error , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[79]  Günther Greiner,et al.  Reconstructing Animated Meshes from Time‐Varying Point Clouds , 2008, Comput. Graph. Forum.

[80]  Jian Zheng,et al.  Robust Non-Rigid Point Set Registration Using Student's-t Mixture Model , 2014, PloS one.

[81]  Heeyoung Kim,et al.  A new metric of absolute percentage error for intermittent demand forecasts , 2016 .

[82]  Jihua Zhu,et al.  Robust non-rigid point set registration via building tree dynamically , 2016, Multimedia Tools and Applications.

[83]  Baba C. Vemuri,et al.  A robust algorithm for point set registration using mixture of Gaussians , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[84]  Liang Li,et al.  Efficient parallel HEVC intra-prediction on many-core processor , 2014 .

[85]  Paul Suetens,et al.  Robust point set registration using EM-ICP with information-theoretically optimal outlier handling , 2011, CVPR 2011.

[86]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[87]  Marc Levoy,et al.  Geometrically stable sampling for the ICP algorithm , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[88]  Niloy J. Mitra,et al.  Estimating surface normals in noisy point cloud data , 2003, SCG '03.

[89]  Li Xie,et al.  Robust CPD Algorithm for Non-Rigid Point Set Registration Based on Structure Information , 2016, PloS one.

[90]  Vladimir G. Kim,et al.  Blended intrinsic maps , 2011, SIGGRAPH 2011.

[91]  Weidong Yan,et al.  Robust image registration using adaptive coherent point drift method , 2016 .

[92]  Li Ma,et al.  Non-rigid point set registration via coherent spatial mapping , 2015, Signal Process..

[93]  Jun Zhang,et al.  Enhanced coherent point drift algorithm for remote sensing image registration , 2015 .

[94]  Lingyun Huang,et al.  A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP) Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration , 2016, PloS one.

[95]  Gang Sun,et al.  Robust rigid coherent point drift algorithm based on outlier suppression and its application in image matching , 2015 .

[96]  Per Bergström,et al.  Robust registration of surfaces using a refined iterative closest point algorithm with a trust region approach , 2016, Numerical Algorithms.

[97]  Pavel Zemcík,et al.  Intensity-based femoral atlas 2D/3D registration using Levenberg-Marquardt optimisation , 2016, SPIE Medical Imaging.

[98]  Sebastian Thrun,et al.  SCAPE: shape completion and animation of people , 2005, SIGGRAPH 2005.

[99]  Andrew W. Fitzgibbon Robust registration of 2D and 3D point sets , 2003, Image Vis. Comput..

[100]  Jinzhong Yang,et al.  The thin plate spline robust point matching (TPS-RPM) algorithm: A revisit , 2011, Pattern Recognit. Lett..

[101]  T. Funkhouser,et al.  Möbius voting for surface correspondence , 2009, SIGGRAPH 2009.

[102]  Lucila Ohno-Machado,et al.  The use of receiver operating characteristic curves in biomedical informatics , 2005, J. Biomed. Informatics.

[103]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[104]  Alan L. Yuille,et al.  Non-Rigid Point Set Registration by Preserving Global and Local Structures , 2016, IEEE Transactions on Image Processing.

[105]  Weisi Lin,et al.  A closed-form estimate of 3D ICP covariance , 2015, 2015 14th IAPR International Conference on Machine Vision Applications (MVA).

[106]  Andriy Myronenko,et al.  Point Set Registration: Coherent Point Drift , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[107]  Pavel Krsek,et al.  Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm , 2005, Image Vis. Comput..

[108]  Stéphane Mallat,et al.  Solving Inverse Problems With Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity , 2010, IEEE Transactions on Image Processing.

[109]  Yongdong Zhang,et al.  Efficient Parallel Framework for HEVC Motion Estimation on Many-Core Processors , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[110]  Seyyed M. T. Fatemi Ghomi,et al.  A new hybrid algorithm of scatter search and Nelder-Mead algorithms to optimize joint economic lot sizing problem , 2016, J. Comput. Appl. Math..

[111]  Jianru Xue,et al.  New iterative closest point algorithm for isotropic scaling registration of point sets with noise , 2016, J. Vis. Commun. Image Represent..

[112]  J. Demantké,et al.  DIMENSIONALITY BASED SCALE SELECTION IN 3D LIDAR POINT CLOUDS , 2012 .

[113]  Andreas Geiger,et al.  Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[114]  Randal W. Beard,et al.  Convergence and Complexity Analysis of Recursive-RANSAC: A New Multiple Target Tracking Algorithm , 2016, IEEE Transactions on Automatic Control.

[115]  Anand Rangarajan,et al.  A new point matching algorithm for non-rigid registration , 2003, Comput. Vis. Image Underst..

[116]  Q. M. Jonathan Wu,et al.  Fast and Robust Spatially Constrained Gaussian Mixture Model for Image Segmentation , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[117]  Andrew Gardner,et al.  Linear light source reflectometry , 2003, ACM Trans. Graph..

[118]  Josef Pelikán,et al.  Low-rank matrix approximations for Coherent point drift , 2015, Pattern Recognit. Lett..

[119]  Ke Li,et al.  Probability iterative closest point algorithm for m-D point set registration with noise , 2015, Neurocomputing.

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

[121]  Chia-Ling Tsai,et al.  The Edge-Driven Dual-Bootstrap Iterative Closest Point Algorithm for Registration of Multimodal Fluorescein Angiogram Sequence , 2010, IEEE Transactions on Medical Imaging.

[122]  Russell H. Taylor,et al.  Iterative Most-Likely Point Registration (IMLP): A Robust Algorithm for Computing Optimal Shape Alignment , 2015, PloS one.

[123]  Colin Studholme,et al.  Automated 3D Registration of Truncated MR and CT Images of the Head , 1995, BMVC.

[124]  Federico Girosi,et al.  Parallel and Deterministic Algorithms from MRFs: Surface Reconstruction , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[125]  Eric Mjolsness,et al.  New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence , 1998, NIPS.

[126]  Yuan Gao,et al.  A robust and outlier-adaptive method for non-rigid point registration , 2013, Pattern Analysis and Applications.

[127]  Dinggang Shen,et al.  Hierarchical Attribute-Guided Symmetric Diffeomorphic Registration for MR Brain Images , 2012, MICCAI.

[128]  Andrew W. Fitzgibbon,et al.  KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera , 2011, UIST.

[129]  Yongdong Zhang,et al.  A Highly Parallel Framework for HEVC Coding Unit Partitioning Tree Decision on Many-core Processors , 2014, IEEE Signal Processing Letters.

[130]  Yaxin Peng,et al.  LieTrICP: An improvement of trimmed iterative closest point algorithm , 2014, Neurocomputing.

[131]  Fabrice Rossi,et al.  Mean Absolute Percentage Error for regression models , 2016, Neurocomputing.

[132]  Dinggang Shen,et al.  HAMMER: hierarchical attribute matching mechanism for elastic registration , 2002, IEEE Transactions on Medical Imaging.

[133]  Terry M. Peters,et al.  Registration of 3D shapes under anisotropic scaling , 2015, International Journal of Computer Assisted Radiology and Surgery.

[134]  Eric Mjolsness,et al.  Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures , 1996, Neural Computation.

[135]  Hans-Peter Seidel,et al.  Efficient reconstruction of nonrigid shape and motion from real-time 3D scanner data , 2009, TOGS.

[136]  Hamid Reza Karimi,et al.  A robust aerial image registration method using Gaussian mixture models , 2014, Neurocomputing.

[137]  Martial Hebert,et al.  Contextual classification with functional Max-Margin Markov Networks , 2009, CVPR.

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

[139]  Christophe Chefd'Hotel,et al.  Registration of multiple temporally related point sets using a novel variant of the coherent point drift algorithm: application to coronary tree matching , 2013, Medical Imaging.

[140]  Martial Hebert,et al.  Natural terrain classification using three‐dimensional ladar data for ground robot mobility , 2006, J. Field Robotics.

[141]  Xavier Pennec,et al.  Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration , 2002, ECCV.

[142]  Rob J Hyndman,et al.  Another look at measures of forecast accuracy , 2006 .

[143]  Deyu Meng,et al.  Robust registration of partially overlapping point sets via genetic algorithm with growth operator , 2014, IET Image Process..

[144]  Joachim Hertzberg,et al.  Automatic construction of polygonal maps from point cloud data , 2010, 2010 IEEE Safety Security and Rescue Robotics.

[145]  Gary K. L. Tam,et al.  Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid , 2013, IEEE Transactions on Visualization and Computer Graphics.

[146]  Leonidas J. Guibas,et al.  Robust single-view geometry and motion reconstruction , 2009, SIGGRAPH 2009.

[147]  Alan L. Yuille,et al.  The invisible hand algorithm: Solving the assignment problem with statistical physics , 1994, Neural Networks.

[148]  David S. Doermann,et al.  Robust point matching for nonrigid shapes by preserving local neighborhood structures , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[149]  Kyle Klein,et al.  Nelder-Mead Simplex Optimization Routine for Large-Scale Problems: A Distributed Memory Implementation , 2013 .