Search results for "Rigid transformation"
showing 3 items of 3 documents
Conservative swept volume boundary approximation
2010
We present a novel technique for approximating the boundary of a swept volume. The generator given by an input triangle mesh is rendered under all rigid transformations of a discrete trajectory. We use a special shader program that creates offset geometry of each triangle on the fly, thus guaranteeing a conservative rasterization and correct depth values. Utilizing rasterization mechanisms and the depth buffer we then get a conservative voxelization of the swept volume (SV) and can extract a triangle mesh from its surface. This mesh is simplified maintaining conservativeness as well as an error bound measured in terms of the one-sided Hausdorff distance. For this we introduce a new techniqu…
Efficient computation of root mean square deviations under rigid transformations
2013
The computation of root mean square deviations (RMSD) is an important step in many bioinformatics applications. If approached naively, each RMSD computation takes time linear in the number of atoms. In addition, a careful implementation is required to achieve numerical stability, which further increases runtimes. In practice, the structural variations under consideration are often induced by rigid transformations of the protein, or are at least dominated by a rigid component. In this work, we show how RMSD values resulting from rigid transformations can be computed in constant time from the protein's covariance matrix, which can be precomputed in linear time. As a typical application scenar…
Effective and Efficient Interpolation for Mutual Information based Multimodality Elastic Image Registration
2009
Mutual information (MI) is a popular similarity metric for multimodality image registration purpose. However, it is negatively influenced by artifacts due to interpolation effects. As a result, registration algorithms performance could be affected. In this paper a novel interpolation scheme is presented. It is both effective and efficient. Effective because it limits the presence of local maxima in the mutual information curve, efficient because it is simple to compute being based on simple and optimized distance measures. The method is validated and compared against other techniques both from performance and time complexity persepectives. Differently from other reference works, which perfo…