Mark C. Surles. An algorithm for linear complexity for interactive, physically-based modelling of large proteins. Computer Graphics, 26(2):221--230, 1992. Proceedings SIGGRAPH '92. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Supporting Numerical Computations in Interactive Contexts - Gleicher, Witkin (1993) (6 citations) (Correct)
....21] Related to the methods of physical simulation are those of constrained optimization. Performing these computations at interactive rates permits using these techniques for interaction and animation problems, such as modeling free form surfaces[8, 32] experimenting with molecular structures[28], solving physical motion control problems[34] positioning virtual cameras[13] and exploring toleranced behavior[24] Since the earliest interactive graphical systems[29] constraints have been used to aid in the manipulation of geometry. From the early systems, numerical techniques to solve ....
....linear equations formed with the Jacobian of the constraint equation. In solving these equations, it is important to exploit sparsity to achieve interactive performance and scalability. Because of the dynamic nature of the problems, systems cannot extensively pre analyze the sparsity, as done in [28]. Instead, like [22] and [26] we use a conjugate gradient solver which is an iterative method and therefore allows some control of the tradeoff between performance and accuracy. We also use damping techniques, similar to those discussed in [31] or used in the LevenbergMarquardt Method[23] ....
Mark C. Surles. An algorithm for linear complexity for interactive, physically-based modelling of large proteins. Computer Graphics, 26(2):221--230, 1992. Proceedings SIGGRAPH '92.
Practical Issues in Graphical Constraints - Gleicher (1994) (8 citations) (Correct)
....the complexity can be lower. Because each constraint only affects at most a small constant number of objects, the matrices only have O(n) entries in them, and can therefore be solved in O(n 2 ) time[22] For certain classes of constraint problems, the linear system can be solved in linear time[24]. To maintain interactive performance, it is critical to reduce the complexity of solving algorithm by exploiting the sparsity of the systems which are solved. However, without severely restricting the class of models which the user can build, this still leaves greater than linear complexity. ....
Mark C. Surles. An algorithm for linear complexity for interactive, physically-based modelling of large proteins. Computer Graphics, 26(2):221--230, 1992. Proceedings SIGGRAPH '92.
Practical Issues in Graphical Constraints - Gleicher (1994) (8 citations) (Correct)
....the corresponding row of the matrix can only have a similarly small number of entries. Therefore, the matrices only have O(n) entries in them, and can the linear systems can be solved in O(n 2 ) time[26] For certain classes of constraint problems, the linear system can be solved in linear time[28]. To maintain interactive performance, it is critical to reduce the complexity of solving algorithm by exploiting the sparsity of the systems which are solved. However, without severely restricting the class of models which the user can build, this still leaves greater than linear complexity. ....
Mark C. Surles. An algorithm for linear complexity for interactive, physically-based modelling of large proteins. Computer Graphics, 26(2):221--230, 1992. Proceedings SIGGRAPH '92.
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