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Thesis (M.S.)--University of Missouri-Columbia, 2008. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on September 19, 2008) Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (p. [120]-122).

The implicit function model is nowadays generally applied to a lot of fields that need 3D, such as computer game, cartoon or for specially effect film. So far, most hardware are still to support the polygon-mesh model but not implicit function model, so polygon-mesh model is still the mainstream of computer graphics. However, translation between the two representation models becomes a new research topic. This paper presents a new method to translate the triangles mesh model into the implicit functions model. The main concept is to use the binary space-partitioning tree to divide the points and patches in the triangle mesh model to create a hierarchical structure. For each leaf node in this hierarchical structure, we would generate a corresponding implicit function. These implicit functions are generated by the genetic algorithm. And the internal nodes in this hierarchical structure are blended by the blending operators. The blending operators make the surface become smooth and continual. The method we proposed reduces the data in a large amount because we only save the coefficients of the implicit surface. And the genetic algorithm can avoid the high computing complexity.

No description available.

Thesis (Ph.D.)--Tufts University, 1992. / Submitted to the Dept. of Mechanical Engineering. Adviser: Vincent P. Manno. Includes bibliographical references (leaves 183-193). Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Made available in DSpace on 2014-06-11T19:22:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-05-12Bitstream added on 2014-06-13T18:48:40Z : No. of bitstreams: 1 denadai_d_me_sjrp.pdf: 370065 bytes, checksum: 6db2aacdc27e3eb4ca5f48d683ca1d56 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Neste trabalho provamos a existência de controle aproximado para certos sistemas não-lineares de equaçõ es diferenciais ordinárias de entrada e saída únicas e múltiplas. Utilizamos como técnica funções ou aplicações implícitas globais. / In this work we prove the existence of approximate control for certain nonlinear sys-tems of ordinary differential equations of single-input single-output and multi-input multi-output. We use global implicit functions or mappings.

Surface reconstruction of anatomical structures is an integral part of medical modeling. Contour information is extracted from serial cross-sections of tissue data and is stored as "slice" files. Although there are several reasonably efficient triangulation algorithms that reconstruct surfaces from slice data, the models generated from them have a jagged or faceted appearance due to the large inter-slice distance created by the sectioning process. Moreover, inconsistencies in user input aggravate the problem. So, we created a method that reduces inter-slice distance, as well as ignores the inconsistencies in the user input. Our method called the piecewise weighted implicit functions, is based on the approach of weighting smaller implicit functions. It takes only a few slices at a time to construct the implicit function. This method is based on a technique called variational interpolation. <p> Other approaches based on variational interpolation have the disadvantage of becoming unstable when the model is quite large with more than a few thousand constraint points. Furthermore, tracing the intermediate contours becomes expensive for large models. Even though some fast fitting methods handle such instability problems, there is no apparent improvement in contour tracing time, because, the value of each data point on the contour boundary is evaluated using a single large implicit function that essentially uses all constraint points. Our method handles both these problems using a sliding window approach. As our method uses only a local domain to construct each implicit function, it achieves a considerable run-time saving over the other methods. The resulting software produces interpolated models from large data sets in a few minutes on an ordinary desktop computer.

Surface reconstruction of anatomical structures is an integral part of medical modeling. Contour information is extracted from serial cross-sections of tissue data and is stored as "slice" files. Although there are several reasonably efficient triangulation algorithms that reconstruct surfaces from slice data, the models generated from them have a jagged or faceted appearance due to the large inter-slice distance created by the sectioning process. Moreover, inconsistencies in user input aggravate the problem. So, we created a method that reduces inter-slice distance, as well as ignores the inconsistencies in the user input. Our method called the piecewise weighted implicit functions, is based on the approach of weighting smaller implicit functions. It takes only a few slices at a time to construct the implicit function. This method is based on a technique called variational interpolation. <p> Other approaches based on variational interpolation have the disadvantage of becoming unstable when the model is quite large with more than a few thousand constraint points. Furthermore, tracing the intermediate contours becomes expensive for large models. Even though some fast fitting methods handle such instability problems, there is no apparent improvement in contour tracing time, because, the value of each data point on the contour boundary is evaluated using a single large implicit function that essentially uses all constraint points. Our method handles both these problems using a sliding window approach. As our method uses only a local domain to construct each implicit function, it achieves a considerable run-time saving over the other methods. The resulting software produces interpolated models from large data sets in a few minutes on an ordinary desktop computer.