Accurate and robust registration for in-hand modeling

We present fast 3D surface registration methods for in-hand modeling. This allows users to scan complete objects swiftly by simply turning them around in front of the scanner. The paper makes two main contributions. First, we propose an efficient method for detecting registration failures, which is a vital property of any automatic modeling system. Our method is based on two different consistency tests, one based on geometry and one based on texture. Second, we extend ICP by three additional fast registration methods for both coarse and fine alignment based on both texture and geometry. Each of those methods brings in additional information that can compensate for ambiguities in the other cues. Together, they allow for the robust reconstruction of a large variety of objects with different geometric and photometric properties. Finally, we show how both failure detection and fast registration can be combined in a practical and robust in-hand modeling system that operates at interactive frame rates.

[1]  Jean-Daniel Deschênes,et al.  A unified representation for interactive 3D modeling , 2004 .

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

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

[4]  Leonidas J. Guibas,et al.  Robust global registration , 2005, SGP '05.

[5]  Til Aach,et al.  Illumination-Invariant Change Detection Using a Statistical Colinearity Criterion , 2001, DAGM-Symposium.

[6]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[7]  Michael G. Strintzis,et al.  This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE Snapshots: A Novel Local Surface , 2022 .

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

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

[10]  Sang Wook Lee,et al.  Range data registration using photometric features , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

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

[12]  Gérard G. Medioni,et al.  Object modeling by registration of multiple range images , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[13]  Andrew E. Johnson,et al.  Registration and integration of textured 3-D data , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[14]  Jan-Michael Frahm,et al.  Real-Time Visibility-Based Fusion of Depth Maps , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[15]  Luc Van Gool,et al.  Online 3D acquisition and model integration , 2003 .

[16]  Luc Van Gool,et al.  Fast 3D Scanning with Automatic Motion Compensation , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[17]  James M. Rehg,et al.  Statistical Color Models with Application to Skin Detection , 2004, International Journal of Computer Vision.

[18]  Song Zhang,et al.  High-Resolution, Real-time 3D Shape Acquisition , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[19]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[20]  K. Nechvíle The High Resolution , 2005 .

[21]  Holly E. Rushmeier,et al.  High-Quality Texture Reconstruction from Multiple Scans , 2001, IEEE Trans. Vis. Comput. Graph..

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

[23]  Holly E. Rushmeier,et al.  The 3D Model Acquisition Pipeline , 2002, Comput. Graph. Forum.

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

[25]  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..

[26]  Marc Levoy,et al.  Real-time 3D model acquisition , 2002, ACM Trans. Graph..

[27]  Robert C. Bolles,et al.  3DPO: A Three- Dimensional Part Orientation System , 1986, IJCAI.

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

[29]  Igor Guskov,et al.  Multi-scale features for approximate alignment of point-based surfaces , 2005, SGP '05.