Interactive Hausdorff Distance Computation for General Pohygonal Models

We present a simple algorithm to compute the Hausdorff distance between complicated, polygonal models at interactive rates. The algorithm requires no assumptions about the underlying topology and geometry. To avoid the high computational and implementation complexity of exact Hausdorff distance calculation, we approximate the Hausdorff distance within a user-specified error bound. The main ingredient of our approximation algorithm is a novel polygon subdivision scheme, called Voronoi subdivision, combined with culling between the models based on bounding volume hierarchy (BVH). This cross-culling method relies on tight yet simple computation of bounds on the Hausdorff distance, and it discards unnecessary polygon pairs from each of the input models alternatively based on the distance bounds. This algorithm can approximate the Hausdorff distance between polygonal models consisting of tens of thousands triangles with a small error bound in real-time, and outperforms the existing algorithm by more than an order of magnitude. We apply our Hausdorff distance algorithm to the measurement of shape similarity, and the computation of penetration depth for physically-based animation. In particular, the penetration depth computation using Hausdorff distance runs at highly interactive rates for complicated dynamics scene.

[1]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[2]  Dinesh Manocha,et al.  Generalized penetration depth computation , 2007, Comput. Aided Des..

[3]  Ingo Wald,et al.  Ray tracing deformable scenes using dynamic bounding volume hierarchies , 2007, TOGS.

[4]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Klaus J. Kirchberg,et al.  Robust Face Detection Using the Hausdorff Distance , 2001, AVBPA.

[6]  Michael T. Goodrich,et al.  Geometric Pattern Matching Under Euclidean Motion , 1993, Comput. Geom..

[7]  Mario A. López,et al.  Hausdorff approximation of 3D convex polytopes , 2008, Inf. Process. Lett..

[8]  Dinesh Manocha,et al.  Simplification envelopes , 1996, SIGGRAPH.

[9]  Touradj Ebrahimi,et al.  MESH: measuring errors between surfaces using the Hausdorff distance , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[10]  Dinesh Manocha,et al.  Fast distance queries with rectangular swept sphere volumes , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[11]  Helmut Alt,et al.  Approximate matching of polygonal shapes , 1995, SCG '91.

[12]  Dinesh Manocha,et al.  Accurate Minkowski sum approximation of polyhedral models , 2004, 12th Pacific Conference on Computer Graphics and Applications, 2004. PG 2004. Proceedings..

[13]  Jane Wilhelms,et al.  Collision Detection and Response for Computer Animation , 1988, SIGGRAPH.

[14]  Ming C. Lin,et al.  Accurate and Fast Proximity Queries Between Polyhedra Using Convex Surface Decomposition , 2001, Comput. Graph. Forum.

[15]  H. Alt,et al.  Computing the Hausdorff Distance of Geometric Patterns and Shapes , 2003 .

[16]  Micha Sharir,et al.  Hausdorff distance under translation for points and balls , 2003, TALG.

[17]  Dinesh Manocha,et al.  Collision and Proximity Queries , 2004, Handbook of Discrete and Computational Geometry, 2nd Ed..

[18]  Leonidas J. Guibas,et al.  Discrete Geometric Shapes: Matching, Interpolation, and Approximation , 2000, Handbook of Computational Geometry.

[19]  Dinesh Manocha,et al.  Fast penetration depth computation for physically-based animation , 2002, SCA '02.

[20]  Micha Sharir,et al.  The upper envelope of voronoi surfaces and its applications , 1993, Discret. Comput. Geom..

[21]  Ming C. Lin,et al.  Fast penetration depth estimation for elastic bodies using deformed distance fields , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[22]  Mikhail J. Atallah,et al.  A Linear Time Algorithm for the Hausdorff Distance Between Convex Polygons , 1983, Inf. Process. Lett..

[23]  Ronald Fedkiw,et al.  Nonconvex rigid bodies with stacking , 2003, ACM Trans. Graph..

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

[25]  William Rucklidge,et al.  Lower bounds for the complexity of the graph of the Hausdorff distance as a function of transformation , 1996, Discret. Comput. Geom..

[26]  Bernardo Llanas,et al.  Efficient Computation of the Hausdorff Distance Between Polytopes by Exterior Random Covering , 2005, Comput. Optim. Appl..

[27]  Joseph S. B. Mitchell,et al.  Approximate Geometric Pattern Matching Under Rigid Motions , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Kurt Mehlhorn,et al.  Classroom Examples of Robustness Problems in Geometric Computations , 2004, ESA.

[29]  Stéphane Redon,et al.  Fast continuous collision detection and handling for desktop virtual prototyping , 2004, Virtual Reality.

[30]  Marc Alexa,et al.  Computing and Rendering Point Set Surfaces , 2003, IEEE Trans. Vis. Comput. Graph..

[31]  Jon M. Kleinberg,et al.  On dynamic Voronoi diagrams and the minimum Hausdorff distance for point sets under Euclidean motion in the plane , 1992, SCG '92.

[32]  Gerhard Hippmann,et al.  An Algorithm for Compliant Contact Between Complexly Shaped Bodies , 2004 .

[33]  Michael Garland,et al.  Surface simplification using quadric error metrics , 1997, SIGGRAPH.

[34]  M. Godau On the complexity of measuring the similarity between geometric objects in higher dimensions , 1999 .