Amitabh Varshney

Mesh saliency

Research over the last decade has built a solid mathematical foundation for representation and analysis of 3D meshes in graphics and geometric modeling. Much of this work however does not explicitly incorporate models of low-level human visual attention. In this paper we introduce the idea of mesh saliency as a measure of regional importance for graphics meshes. Our notion of saliency is inspired by low-level human visual system cues. We define mesh saliency in a scale-dependent manner using a center-surround operator on Gaussian-weighted mean curvatures. We observe that such a definition of mesh saliency is able to capture what most would classify as visually interesting regions on a mesh. The human-perception-inspired importance measure computed by our mesh saliency operator results in more visually pleasing results in processing and viewing of 3D meshes. compared to using a purely geometric measure of shape. such as curvature. We discuss how mesh saliency can be incorporated in graphics applications such as mesh simplification and viewpoint selection and present examples that show visually appealing results from using mesh saliency.

Simplification envelopes

We propose the idea of simplification envelopes for generating a hierarchy of level-of-detail approximations for a given polygonal model. Our approach guarantees that all points of an approximation are within a user-specifiable distance from the original model and that all points of the original model are within a distance from the approximation. Simplificationenvelopes provide a general framework within which a large collection of existing simplification algorithms can run. We demonstrate this technique in conjunction with two algorithms, one local, the other global. The local algorithm provides a fast method for generating approximations to large input meshes (at least hundreds of thousands of triangles). The global algorithm provides the opportunity to avoid local “minima” and possibly achieve better simplifications as a result. Each approximation attempts to minimize the total number of polygons required to satisfy the above constraint. The key advantages of our approach are: General technique providing guaranteed error bounds for genus-preserving simplification Automation of both the simplification process and the selection of appropriate viewing distances Prevention of self-intersection Preservation of sharp features Allows variation of approximation distance across different portions of a model CR

Dynamic view-dependent simplification for polygonal models

Presents an algorithm for performing view-dependent simplifications of a triangulated polygonal model in real-time. The simplifications are dependent on viewing direction, lighting and visibility, and are performed by taking advantage of image-space, object-space and frame-to-frame coherences. A continuous level-of-detail representation for an object is first constructed off-line. This representation is then used at run-time to guide the selection of appropriate triangles for display. The list of displayed triangles is updated incrementally from one frame to the next. Our approach is more effective than the current level-of-detail-based rendering approaches for most scientific visualization applications where there are a limited number of highly complex objects that stay relatively close to the viewer.

High-throughput sequence alignment using Graphics Processing Units

BackgroundThe recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies.ResultsThis paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs) in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA) from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies.ConclusionMUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.

Adaptive real-time level-of-detail based rendering for polygonal models

We present an algorithm for performing adaptive real-time level-of-detail-based rendering for triangulated polygonal models. The simplifications are dependent on viewing direction, lighting, and visibility and are performed by taking advantage of image-space, object-space, and frame-to-frame coherences. In contrast to the traditional approaches of precomputing a fixed number of level-of-detail representations for a given object, our approach involves statically generating a continuous level-of-detail representation for the object. This representation is then used at run time to guide the selection of appropriate triangles for display. The list of displayed triangles is updated incrementally from one frame to the next. Our approach is more effective than the current level-of-detail-based rendering approaches for most scientific visualization applications, where there are a limited number of highly complex objects that stay relatively close to the viewer. Our approach is applicable for scalar (such as distance from the viewer) as well as vector (such as normal direction) attributes.

Optimizing triangle strips for fast rendering

Almost all scientific visualization involving surfaces is currently done via triangles. The speed at which such triangulated surfaces can be displayed is crucial to interactive visualization and is bounded by the rate at which triangulated data can be sent to the graphics subsystem for rendering. Partitioning polygonal models into triangle strips can significantly reduce rendering times over transmitting each triangle individually. We present new and efficient algorithms for constructing triangle strips from partially triangulated models, and experimental results showing these strips are on average 15% better than those from previous codes. Further, we study the impact of larger buffer sizes and various queuing disciplines on the effectiveness of triangle strips.

Generalized View-Dependent Simplification

We propose a technique for performing view‐dependent geometry and topology simplifications for level‐of‐detail‐based renderings of large models. The algorithm proceeds by preprocessing the input dataset into a binary tree, the view‐dependence tree of general vertex‐pair collapses. A subset of the Delaunay edges is used to limit the number of vertex pairs considered for topology simplification. Dependencies to avoid mesh foldovers in manifold regions of the input object are stored in the view‐dependence tree in an implicit fashion. We have observed that this not only reduces the space requirements by a factor of two, it also highly localizes the memory accesses at run time. The view‐dependence tree is used at run time to generate the triangles for display. We also propose a cubic‐spline‐based distance metric that can be used to unify the geometry and topology simplifications by considering the vertex positions and normals in an integrated manner.

Computing smooth molecular surfaces

We consider how we set out to formulate a parallel analytical molecular surface algorithm that has expected linear complexity with respect to the total number of atoms in a molecule. To achieve this goal, we avoided computing the complete 3D regular triangulation over the entire set of atoms, a process that takes time O(n log n), where n is the number of atoms in the molecule. We aim to compute and display these surfaces at interactive rates, by taking advantage of advances in computational geometry, making further algorithmic improvements and parallelizing the computations.<<ETX>>

Voxel based object simplification

Presents a simple, robust and practical method for object simplification for applications where gradual elimination of high-frequency details is desired. This is accomplished by sampling and low-pass filtering the object into multi-resolution volume buffers and applying the marching cubes algorithm to generate a multi-resolution triangle-mesh hierarchy. Our method simplifies the genus of objects and can also help existing object simplification algorithms achieve better results. At each level of detail, a multi-layered mesh can be used for an optional and efficient antialiased rendering.

Navigating static environments using image-space simplification and morphing

We present a z-buffered image-space-based rendering technique that allows navigation in complex static environments. The rendering speed is relatively insensitive to the complexity of the scene as the rendering is performed a priori, and the scene is converted into a bounded complexity representation in the image space. Realtime performance is attained by using hardware texture mapping to implement the image-space warping and hardware affine transformations to compute the viewpoint–dependent warping function. Our proposed method correctly simulates the kinetic depth effect (parallax), occlusion, and can resolve the missing visibility information by combining z-buffered environment maps from multiple viewpoints. CR