Closed-Form Solutions for Physically Based Shape Modeling and Recognition

The authors present a closed-form, physically based solution for recovering a three-dimensional (3-D) solid model from collections of 3-D surface measurements. Given a sufficient number of independent measurements, the solution is overconstrained and unique except for rotational symmetries. The proposed approach is based on the finite element method (FEM) and parametric solid modeling using implicit functions. This approach provides both the convenience of parametric modeling and the expressiveness of the physically based mesh formulation and, in addition, can provide great accuracy at physical simulation. A physically based object-recognition method that allows simple, closed-form comparisons of recovered 3-D solid models is presented. The performance of these methods is evaluated using both synthetic range data with various signal-to-noise ratios and using laser rangefinder data. >

[1]  L. Segerlind Applied Finite Element Analysis , 1976 .

[2]  D. Marr,et al.  Representation and recognition of the spatial organization of three-dimensional shapes , 1978, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[3]  H. Saunders,et al.  Finite element procedures in engineering analysis , 1982 .

[4]  Michael R. Lowry,et al.  Learning Physical Descriptions From Functional Definitions, Examples, and Precedents , 1983, AAAI.

[5]  Donald D. Hoffman,et al.  Parts of recognition , 1984, Cognition.

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

[7]  A. Pentland Recognition by Parts , 1987 .

[8]  Terrance E. Boult,et al.  Recovery of superquadrics from depth information , 1987 .

[9]  I. Biederman Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.

[10]  Ramakant Nevatia,et al.  Using Perceptual Organization to Extract 3-D Structures , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Alex Pentland,et al.  Part Segmentation for Object Recognition , 1989, Neural Computation.

[12]  Alex Pentland,et al.  Good vibrations: modal dynamics for graphics and animation , 1989, SIGGRAPH.

[13]  Irfan Essa,et al.  Contact detection, collision forces and friction for physically based virtual world modeling , 1990 .

[14]  Alex Pentland,et al.  The ThingWorld modeling system: virtual sculpting by modal forces , 1990, I3D '90.

[15]  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..

[16]  Alex Pentland,et al.  Segmentation by minimal description , 1990, [1990] Proceedings Third International Conference on Computer Vision.