Efficient partial-surface registration for 3D objects

We present a new method for three-dimensional partial-surface registration that utilizes both regional surface properties and shape rigidity constraint to align a partial object surface and its corresponding complete surface. The statistical properties of the vertices on the object surface are first computed and compared with each other to find the initial candidate correspondences. We use the overall object-shape rigidity constraint and a clustering method to obtain an approximation of the transformation parameters while, at the same time, rejecting correspondence outliers. The transformation parameters can be further refined with an iterative approach. The algorithm does not require any feature extraction or initial pose estimation, and is especially applicable when the object surfaces are formed by a large number of vertices, smooth with few salient features, and contain many regionally similar surface patches. Experiments confirm that the proposed scheme can achieve accurate registration results in an efficient manner.

[1]  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..

[2]  Michael A. Greenspan,et al.  Approximate k-d tree search for efficient ICP , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

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

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

[5]  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).

[6]  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.

[7]  Aly A. Farag,et al.  Surfacing Signatures: An Orientation Independent Free-Form Surface Representation Scheme for the Purpose of Objects Registration and Matching , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

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

[9]  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..

[10]  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).

[11]  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.

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

[13]  Max A. Viergever,et al.  Evaluation of Ridge Seeking Operators for Multimodality Medical Image Matching , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

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

[15]  Yi Ping Hung,et al.  A fast automatic method for registration of partially-overlapping range images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

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

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

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

[19]  Liu Jian.  Multi-Resolution Mesh Based 3D Object Recognition , 2001 .

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

[21]  George C. Stockman,et al.  Object recognition and localization via pose clustering , 1987, Comput. Vis. Graph. Image Process..

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

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

[24]  Pavel Krsek,et al.  Differential Invariants as the Base of Triangulated Surface Registration , 2002, Comput. Vis. Image Underst..

[25]  Ramesh C. Jain,et al.  Three-dimensional object recognition , 1985, CSUR.

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

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

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

[29]  Richard Szeliski,et al.  Recovering the Position and Orientation of Free-Form Objects from Image Contours Using 3D Distance Maps , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

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

[31]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using orthonormal matrices , 1988 .

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

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

[34]  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.

[35]  Robert Bergevin,et al.  Registering Range Views of Multipart Objects , 1995, Comput. Vis. Image Underst..

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

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

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

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