High-level model acquisition from range images

Abstract Automatic extraction of cad descriptions which are ultimately intended for human manipulation requires the accurate inference of geometric and topological information. We present a system which applies segmentation techniques from computer vision to automatically extract cad models from range images of parts with curved surfaces. The segmentation process is an improvement upon Besl and Jain's variable-order surface fitting (IEEE PAMI, 1988, 10(2), 167–192), extracting general quadric surfaces and planes from the data, with a postprocessing stage to identify surface intersections and to extract a B-rep from the segmented image. We present results on a variety of machined objects, which illustrate the high-level nature of the acquired models, and discuss the numerical accuracy (feature sizes and separations) and the correctness of structural inferences of the system.

[1]  Michel Gay.  Segmentation Using Region Merging with Edges , 1989, Alvey Vision Conference.

[2]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[3]  Robert B. Fisher,et al.  A Comparative Analysis of Algorithms for Determining the Peak Position of a Stripe to Sub-pixel Accuracy , 1991, BMVC.

[4]  Yoshiaki Shirai,et al.  Object Recognition Using Three-Dimensional Information , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Andrew W. Fitzgibbon,et al.  An Experimental Comparison of Range Image Segmentation Algorithms , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Anil K. Jain,et al.  Evidence-Based Recognition of 3-D Objects , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Robert B. Fisher,et al.  Experiments in Curvature-Based Segmentation of Range Data , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Robert C. Bolles,et al.  Perceptual Organization and Curve Partitioning , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Emanuele Trucco,et al.  Computer and Robot Vision , 1995 .

[10]  M. Hebert,et al.  The Representation, Recognition, and Locating of 3-D Objects , 1986 .

[11]  A. Pentland.  Perceptual organization and the representation of natural form , 1987 .

[12]  Gerald J. Agin.  Representation and description of curved objects , 1972 .

[13]  Gabriel Taubin,et al.  Estimation of Planar Curves, Surfaces, and Nonplanar Space Curves Defined by Implicit Equations with Applications to Edge and Range Image Segmentation , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Andrew Fitzgibbon,et al.  Suggestive modeling for machine vision , 1992 .

[15]  Harry Shum,et al.  Virtual reality modeling from a sequence of range images , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[16]  T. Fan.  Describing and Recognizing 3-D Objects Using Surface Properties , 1989, Springer Series in Perception Engineering.

[17]  David Shi Chen,et al.  A Data-Driven Intermediate Level Feature Extraction Algorithm , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Andrew W. Fitzgibbon,et al.  Lack-of-fit Detection using the Run-distribution Test , 1994, ECCV.

[19]  W. Eric L. Grimson,et al.  Finding cylinders in range data , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[20]  Olivier D. Faugeras,et al.  A 3-D Recognition and Positioning Algorithm Using Geometrical Matching Between Primitive Surfaces , 1983, IJCAI.

[21]  Alex Pentland,et al.  Perceptual Organization and the Representation of Natural Form , 1986, Artif. Intell..

[22]  W. Grimson,et al.  Model-Based Recognition and Localization from Sparse Range or Tactile Data , 1984 .

[23]  Pierre Boulanger,et al.  Multiresolution segmentation of range images based on Bayesian decision theory , 1992, Other Conferences.

[24]  Paul J. Besl,et al.  Surfaces in Range Image Understanding , 1988, Springer Series in Perception Engineering.

[25]  Michael Potmesil,et al.  Generating Models of Solid Objects by Matching 3D Surface Segments , 1983, IJCAI.

[26]  R. Fisher.  SMS: a suggestive modelling system for object recognition , 1987, Image Vis. Comput..

[27]  Christopher M. Brown.  Advances in computer vision , 1987 .

[28]  Ruzena Bajcsy,et al.  Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  Andrew W. Fitzgibbon,et al.  A Buyer's Guide to Conic Fitting , 1995, BMVC.

[30]  Thomas C. Henderson,et al.  Feature-based reverse engineering of mechanical parts , 1999, IEEE Trans. Robotics Autom..

[31]  Robert C. Bolles,et al.  A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data , 1981, IJCAI.

[32]  Russell H. Taylor,et al.  Automatic Synthesis of Fine-Motion Strategies for Robots , 1984 .

[33]  John E. Dennis,et al.  An Adaptive Nonlinear Least-Squares Algorithm , 1977, TOMS.

[34]  Josef Kittler,et al.  Depth data segmentation using robust estimation in a hierarchical data structure , 1992 .

[35]  Andrew W. Fitzgibbon,et al.  Invariant Fitting of Arbitrary Single-Extremum Surfaces , 1993, BMVC.

[36]  Ramesh C. Jain,et al.  Segmentation through Variable-Order Surface Fitting , 1988, IEEE Trans. Pattern Anal. Mach. Intell..