Robust and adaptive merge of multiple range images with photometric attribute

In the use of the three-dimensional data obtained from a stereo system, laser range finder, and other equipment, merge processing is important. This paper proposes a new merge method for range images, based on the volume-based technique. In the proposed method, in contrast to the conventional method, the voxels are adaptively segmented according to the curvature of the surface shape to be reconstructed. This helps to represent the geometrical shape efficiently, effectively utilizing the computation resources. In the framework of the proposed merge process, additional features such as color and the laser reflectivity can be added to the three-dimensional geometrical information, which helps to maintain sharp edges in the texture and to perform rendering and the texture mapping effectively. By examining the consensus for both the geometrical shape and the color in the whole framework, the merge is made robust to noise. In this paper, the system is described first, and then the results of application to several kinds of actual data are presented. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(11): 50–60, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20353

[1]  Gang Wang,et al.  From images to models: automatic 3D object model construction from multiple views , 1996, Proceedings of 13th International Conference on Pattern Recognition.

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

[3]  Kiriakos N. Kutulakos,et al.  What Do N Photographs Tell Us about 3D Shape , 1998 .

[4]  Katsushi Ikeuchi,et al.  Simultaneous 2D images and 3D geometric model registration for texture mapping utilizing reflectance attribute , 2002 .

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

[6]  Mohan S. Kankanhalli,et al.  Adaptive marching cubes , 1995, The Visual Computer.

[7]  Hugues Hoppe,et al.  New quadric metric for simplifying meshes with appearance attributes , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[8]  Marc Levoy,et al.  The digital Michelangelo project: 3D scanning of large statues , 2000, SIGGRAPH.

[9]  Thomas Malzbender,et al.  Generalized Voxel Coloring , 1999, Workshop on Vision Algorithms.

[10]  Katsushi Ikeuchi,et al.  Parallel processing of range data merging , 2001 .

[11]  Andrew E. Johnson,et al.  Surface registration by matching oriented points , 1997, Proceedings. International Conference on Recent Advances in 3-D Digital Imaging and Modeling (Cat. No.97TB100134).

[12]  Shree K. Nayar,et al.  Generalization of the Lambertian model and implications for machine vision , 1995, International Journal of Computer Vision.

[13]  Tony DeRose,et al.  Surface reconstruction from unorganized points , 1992, SIGGRAPH.

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

[15]  Ronald N. Perry,et al.  Adaptively sampled distance fields: a general representation of shape for computer graphics , 2000, SIGGRAPH.

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

[17]  Paolo Cignoni,et al.  Metro: Measuring Error on Simplified Surfaces , 1998, Comput. Graph. Forum.

[18]  Michael Garland,et al.  Simplifying surfaces with color and texture using quadric error metrics , 1998, Proceedings Visualization '98 (Cat. No.98CB36276).

[19]  Andrew W. Fitzgibbon,et al.  Simultaneous registration of multiple range views for use in reverse engineering , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[20]  Roni Yagel,et al.  Octree-based decimation of marching cubes surfaces , 1996, Proceedings of Seventh Annual IEEE Visualization '96.

[21]  Adrian Hilton,et al.  Reliable Surface Reconstructiuon from Multiple Range Images , 1996, ECCV.

[22]  Mark D. Wheeler,et al.  Automatic Modeling and Localization for Object Recognition , 1996 .

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

[24]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[25]  Hiromi T. Tanaka Accuracy-Based Sampling and Reconstruction with Adaptive Meshes for Parallel Hierarchical Triangulation , 1995, Comput. Vis. Image Underst..

[26]  Katsushi Ikeuchi,et al.  Eigen-texture method: Appearance compression based on 3D model , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[27]  Katsushi Ikeuchi,et al.  Consensus surfaces for modeling 3D objects from multiple range images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[28]  Jon Louis Bentley,et al.  An Algorithm for Finding Best Matches in Logarithmic Expected Time , 1977, TOMS.

[29]  Marc Levoy,et al.  QSplat: a multiresolution point rendering system for large meshes , 2000, SIGGRAPH.

[30]  Steven M. Seitz,et al.  Photorealistic Scene Reconstruction by Voxel Coloring , 1997, International Journal of Computer Vision.

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