Registration of partially overlapping surfaces by rejection of false point correspondences

We present a new algorithm for the registration of three-dimensional partially overlapping surfaces. It is based on an efficient scheme for the rejection of false point correspondences (correspondence outliers) and does not require initial pose estimation or feature extraction. An initial list of corresponding points is first derived using the regional properties of vertices on both surfaces. From these point correspondences, pairs of corresponding rigid triplets are formed. The normal vectors at the vertices of each corresponding triplet are used to compute the candidate rotations. By clustering the candidate rotation axes and candidate rotation angles separately, a large number of false correspondences are eliminated and an approximate rotation is decided, from which an approximate translation is also obtained. Finally, the optimal transformation parameters are determined by further refining the estimated parameters in an iterative manner. Mathematical analysis and experimental results show that the registration process is fast and accurate even when the objects are regularly shaped and contain many regionally similar surface patches.

[1]  Kenneth I. Joy,et al.  Simplification of Tetrahedral Meshes with Error Bounds , 1999, IEEE Trans. Vis. Comput. Graph..

[2]  Linda G. Shapiro,et al.  A new paradigm for recognizing 3-D objects from range data , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[3]  Marcos A. Rodrigues,et al.  On the representation of rigid body transformations for accurate registration of free-form shapes , 2002, Robotics Auton. Syst..

[4]  Jean-Philippe Thirion,et al.  Extremal points: definition and application to 3D image registration , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

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

[6]  Clark F. Olson,et al.  Efficient Pose Clustering Using a Randomized Algorithm , 1997, International Journal of Computer Vision.

[7]  Shimon Ullman,et al.  Recognizing solid objects by alignment with an image , 1990, International Journal of Computer Vision.

[8]  Andrew E. Johnson,et al.  Surface landmark selection and matching in natural terrain , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[9]  Andrew E. Johnson,et al.  Surface matching for object recognition in complex three-dimensional scenes , 1998, Image Vis. Comput..

[10]  Michael A. Greenspan,et al.  The parallel iterative closest point algorithm , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.

[11]  Yasuhito Suenaga,et al.  A Facsimile-Based Graphics Editing System by Auxiliary Mark Recognition , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Yi-Ping Hung,et al.  RANSAC-Based DARCES: A New Approach to Fast Automatic Registration of Partially Overlapping Range Images , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Haim J. Wolfson,et al.  Geometric hashing: an overview , 1997 .

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

[15]  Geoffrey H. Ball,et al.  ISODATA, A NOVEL METHOD OF DATA ANALYSIS AND PATTERN CLASSIFICATION , 1965 .

[16]  Chitra Dorai,et al.  COSMOS - A Representation Scheme for 3D Free-Form Objects , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Yehezkel Lamdan,et al.  Geometric Hashing: A General And Efficient Model-based Recognition Scheme , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[18]  Patrick J. Flynn,et al.  A Survey Of Free-Form Object Representation and Recognition Techniques , 2001, Comput. Vis. Image Underst..

[19]  Gérard G. Medioni,et al.  Structural Indexing: Efficient 3-D Object Recognition , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Ramesh C. Jain,et al.  Invariant surface characteristics for 3D object recognition in range images , 1985, Comput. Vis. Graph. Image Process..

[21]  Heinz Hügli,et al.  A multi-resolution ICP with heuristic closest point search for fast and robust 3D registration of range images , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[22]  William Grimson,et al.  Object recognition by computer - the role of geometric constraints , 1991 .

[23]  Nasser Khalili,et al.  Multi-scale free-form 3D object recognition using 3D models , 2001, Image Vis. Comput..

[24]  D. Huttenlocher.  Three-Dimensional Recognition of Solid Objects from a Two- Dimensional Image , 1988 .

[25]  Mongi A. Abidi,et al.  Surface matching by 3D point's fingerprint , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[26]  Berthold K. P. Horn.  Relative orientation , 1987, International Journal of Computer Vision.

[27]  Aly A. Farag,et al.  Free-form surface registration using surface signatures , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[28]  Bernd Hamann,et al.  Constructing Hierarchies for Triangle Meshes , 1998, IEEE Trans. Vis. Comput. Graph..

[29]  S. Umeyama,et al.  Least-Squares Estimation of Transformation Parameters Between Two Point Patterns , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[31]  Dongmei Zhang,et al.  Harmonic maps and their applications in surface matching , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[32]  Gabriel Taubin,et al.  Estimating the tensor of curvature of a surface from a polyhedral approximation , 1995, Proceedings of IEEE International Conference on Computer Vision.

[33]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[34]  Katsushi Ikeuchi,et al.  A Spherical Representation for Recognition of Free-Form Surfaces , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[35]  Dongmei Zhang,et al.  Experimental analysis of Harmonic Shape Images , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[36]  Chin Seng Chua,et al.  Point Signatures: A New Representation for 3D Object Recognition , 1997, International Journal of Computer Vision.

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

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

[39]  Larry S. Davis,et al.  Pose Determination of a Three-Dimensional Object Using Triangle Pairs , 1988, IEEE Trans. Pattern Anal. Mach. Intell..