K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. Journal of Information Processing, 12(4):380--393, 1989.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....now become one of the major issue in the eld of computational geometry [4, chap. 10] Some attempts have been made to design geometric algorithms such that robust implementations can be obtained using only the inaccurate but fast arithmetic provided by AEoating point processors (see for examples [17, 18, 15, 13, 10, 11, 8]) Such solutions, although very useful in some domains like solid modeling and CSG applications, are still painful to design and known only for a few geometric problems. Another approach is to turn to exact arithmetic which makes robustness a non issue. The use of exact arithmetic has been ....

K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. J. Inform. Proc., 12(4):380393, 1989.

....in conference papers (Section 4.5) and used in practice. Advantages: can handle any lattice with connected rounding cells (Section 3.1) Introduces minimum geometric and combinatorial error. Simple to use in practice. Disadvantages: not clear how to generalize to three dimensions. CSG Rounding [37]: Given a CSG (constructive solid geometry) representation of an object, round CSG primitives and then reconstruct the tree. Advantages: works in three dimensions. Disadvantages: suitable for set operations and transformations, not decompositions, convex hull, or Minkowski sum. Topology might be ....

K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. J. Inform. Proc., 12(4):380-393, 1989.

....that both algorithms were developed as a means to represent polyhedra; the authors did not set out to explicitly solve the solid reconstruction problem. In the computational geometry and solid modelling communities, there has been a lot of work on the related problem of robust geometric computing [45, 56, 57, 91, 95, 99, 105, 107]. These techniques are not applicable to our problem since they attempt to avoid errors caused by numerical imprecision and cannot clean up already incorrect data. 2.2 Our Approach We have adopted a novel solid based approach that uses region adjacency relationships to compute which regions are ....

K. Sugihara and M. Iri, A solid modelling system free from topological inconsistency, J. Inform. Proc., 12 (1989), 380--393.

....in the eld of computational geometry (for a discussion, see [C 96, chap. 10] Some attempts have been made to design geometric algorithms such that robust implementations can be obtained using only the inaccurate but fast arithmetic provided by AEoating point processors (see for examples [SI89, SI94, Mil89, LM90, Hof89, HHK88, For92] Such solutions, although very useful in some domains like solid modeling and CSG applications, are diOEcult to design and known only for a few geometric problems. Another approach is to turn to exact arithmetic which makes robustness a non issue. The use ....

K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. J. Inform. Proc., 12(4):380393, 1989.

....In Section 6, we discuss techniques that we plan to implement to overcome these limitations. The final section is a brief conclusion. 2 Previous Work In the computational geometry and solid modeling communities, there has been a lot of work on the related problem of robust geometric computing [7, 12, 13, 23, 25, 26, 29, 31]. These techniques are not applicable to our problem since they attempt to avoid errors caused by numerical imprecision and cannot clean up already incorrect data. It has been noted in the literature that there are currently no robust techniques to solve the solid reconstruction problem [10, 17] ....

K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. Journal of Information Processing, 12(4):380--393, 1989.

.... Euclidean space, and set theoretic operations are replaced by their regularized versions [22] Several algorithms exist for solving Boolean operations on polyhedral solids, but not all satisfactorily address the crucial problem of numerical errors that are inherent to floating point computations [7, 10, 11, 19, 20, 21]. In this paper, we present solutions that we have experimented in the implementation of a solid modeler. Our approach is based on a general algorithm and data structure that naturally accommodate non manifold geometric cases. Numerical errors are avoided by the use of a new kind of exact ....

....algorithm, that maintains a consistent geometrical data base. Mantyla and Sulonen [11] ensure topological consistency in their GWB solid modeler by the strict use of Euler operators. However, these operators do not avoid contradictions between numerical and topological data. Sugihara and Iri [21] observe that if the original geometric data are represented in a finite precision, the relative topological configuration of two geometric elements can be computed exactly in some finite precision. They show how it is possible to build an errorfree polyhedral modeler based on trihedral ....

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Sugihara, K and Iri, M. A Solid Modelling System Free From Topological Inconsistency. Research Memorandum RMI 89-03, Dept. of Math. Engr. and Info. Physics, Tokyo University, Japan, 1989.

....in conference papers (Section 4.5) and used in practice. Advantages: can handle any lattice with connected rounding cells (Section 3.1) Introduces minimum geometric and combinatorial error. Simple to use in practice. Disadvantages: not clear how to generalize to three dimensions. CSG Rounding [37]: Given a CSG (constructive solid geometry) representation of an object, round CSG primitives and then reconstruct the tree. Advantages: works in three dimensions. Disadvantages: suitable for set operations and transformations, not decompositions, convex hull, or Minkowski sum. Topology 2 At the ....

K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. J. Inform. Proc., 12(4):380--393, 1989.

....In Section 6, we discuss techniques that we plan to implement to overcome these limitations. The nal section is a brief conclusion. 2 Previous Work In the computational geometry and solid modeling communities, there has been a lot of work on the related problem of robust geometric computing [7, 12, 13, 23, 25, 26, 29, 31]. These techniques are not applicable to our problem since they attempt to avoid errors caused by numerical imprecision and cannot clean up already incorrect data. It has been noted in the literature that there are currently no robust techniques to solve the solid reconstruction problem [10, 17] ....

K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. Journal of Information Processing, 12(4):380393, 1989.

....most likely be cumbersome, and as such original numbers may themselves be the results of imprecise computations. Regular alignment: inputs are aligned on the nearest multiple of a given unit. For instance, if the unit were 1, floating point numbers would be aligned on the nearest integer (cf. [16]) Adaptive alignment: the inputs are aligned on the nearest rational number for a given precision. Several techniques may be used for this purpose, among which continued fractions expansion (CFE) 9] This method yields the fastest algorithms and the most concise rational numbers for a given ....

K. Sugihara and M. Iri. A Solid Modelling System Free from Topological Inconsistencies. Research Memorandum, RM 89-03, University of Tokyo, 1989.

No context found.

K. Sugihara and M. Iri. A solid modelling system free from topological inconsistency. Journal of Information Processing, 12(4):380--393, 1989.

No context found.

K. Sugihara and M. Iri, "A solid modelling system free from topological inconsistency", Journal of Information Processing, Vol. 12, No. 4, pp. 380-393, 1989.

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