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Graphics Lunch - Spring, 2006

Graphics Lunch is a forum for informal and formal discussions over lunch for those interested in graphics and visualization issues at Maryland. It also serves as a forum for talks from visitors to our lab about their recent research in graphics and visualization. Students and faculty can use this venue to practise and prepare for their conference papers, discuss recent and upcoming papers and conferences, or inform others about graphics and visualization news. Meetings are held on Mondays from 12:00pm to 1:30pm in AVW 4185 .

Announcements regarding Graphics Lunch will be sent to the graphics-local mailing list. You may join this list at http://www.cs.umd.edu/mailman/listinfo/graphics-local.

  Recent Seminars

May 15, 2006  Enjoying your work, what every computer scientist should know about games
Presented By Bretton Wade, Firaxis Games
Comments Graphics Seminar Series (Held in CSIC 1122)

Computer games are big business, and with tremendous investments come serious work. Large, multi-discipline teams work to tight schedules on state of the art hardware using state of the art software tools, and we have fun doing it! This talk will cover where game development has been, where it is now, and where it is going. I will explain how games get made, and what tools, techniques, and knowledge make for successful game developers.

May 8, 2006  Information Visualization for High-Dimensional Spaces
Presented By Ben Shneiderman, University of Maryland, College Park
Comments Graphics Seminar Series

Interactive information visualization provide researchers with remarkable tools for discovery. By combining powerful data mining methods with user-controlled interfaces, users are beginning to benefit from these potent telescopes for high-dimensional spaces. They can begin with an overview, zoom in on areas of interest, filter out unwanted items, and then click for details-on-demand. With careful design and efficient algorithms, the dynamic queries approach to data exploration can provide 100msec updates even for million-record databases. This talk will start by reviewing the growing commercial success stories such as www.spotfire.com , www.smartmoney.com/marketmap , and www.hivegroup.com . Then it will cover recent research progress for visual exploration of large time series data applied to financial, Ebay auction, and genomic data (www.cs.umd.edu/hcil/timesearcher ). Our next step was to combine these key ideas to produce the Hierarchical Clustering Explorer 3.0 that now includes the rank-by-feature framework (www.cs.umd.edu/hcil/hce ). By judiciously choosing from appropriate ranking criteria for low-dimensional axis-parallel projections, users can locate desired features of higher dimensional spaces. Demonstrations will be shown.

May 1, 2006  Decomposition and Compression of Regularly Sampled Geometry
Presented By Kenny Weiss, University of Maryland, College Park
Comments Graphics Seminar Series

With the size of geometric datasets growing even faster than the speed of processors (including GPUs) it is becoming increasingly important to find compression schemes for geometric data. Additionally, laser scanned geometry needs to be processed to regain an object's topology. Geometric remeshing is a technique that can be helpful in fixing problematic regions of the scanned geometry and in compressing overly sampled regions. We will present Geometry Images, a recent method of regularly sampling geometric data as well as some of its variants. Once geometry has been regularly resampled, we can apply signal processing and matrix/tensor decomposition schemes to the data to yeild significant compression rates without much loss in geometric integrity. We present two related decomposition schemes for regularly sampled geometric datasets: Singular Value Decomposition (SVD) and Semi Discrete Decomposition (SDD) and present some results comparing compression rates to data integrity on geometry images. We also suggest other domains to apply these techniques.

April 24, 2006  Topological decomposition of 3D non-manifold simplicial complexes and supporting data structure (DLVG).
Presented By Lucas Vaczlavik, University of Maryland, College Park
Comments Graphics Seminar Series

An efficient algorithm for the decomposition of the initial 3D complex (non-manifold) into highly connected components (IQMs - almost manifolds) by breaking down the complex at non-manifold parts. Presentation of a 2 level data structure (Double Level Vertex Graph) which supports this decomposition, is scalable and which allows efficient retrieval of all other topological relations. The high level data structure is a hypergraph which represents the relations between the highly connected components (pseudo manifolds or IQMs) and a low level data structure for storing these components. The nodes of the hypergraph correspond to the IQMs, while the hyperarcs correspond to the non-manifold edges and vertices.

April 17, 2006  A Novel Information-Aware Octree for the Visualization of Large-scale Time-Varying data.
Presented By Jusub Kim, University of Maryland, College Park
Comments Graphics Seminar Series

Large scale scientific simulations are increasingly generating very large data sets that present substantial challenges to current visualization systems. In this paper, we develop a new scalable and efficient scheme for the visual exploration of 4-D isosurfaces of time varying data by rendering the 3-D isosurfaces obtained through an arbitrary axis-parallel hyperplane cut. The new scheme is based on: (i) a new 4-D hierarchical indexing structure, called Information-Aware Octree; (ii) a controllable delayed fetching technique; and (iii) an optimized data layout. Together, these techniques enable efficient and scalable out-of-core visualization of large scale time varying data sets. We introduce an entropy-based dimension integration technique by which the relative resolutions of the spatial and temporal dimensions are established, and use this information to design a compact size 4-D hierarchical indexing structure. We also present scalable and efficient techniques for out-of-core rendering. Compared with previous algorithms for constructing 4-D isosurfaces, our scheme is substantially faster and requires much less memory. Compared to the temporal Branch-On-Need octree (T-BON), which can only handle a subset of our queries, our indexing structure is an order of magnitude smaller and is at least as effective in dealing with the queries that the T-BON can handle. We have tested our scheme on two large time-varying data sets and obtained very good performance for a wide range of isosurface extraction queries using an order of magnitude smaller indexing structures than previous techniques. In particular, we can generate isosurfaces at intermediate time steps very quickly.

April 10, 2006  Vertex Transformation Streams
Presented By Youngmin Kim, University of Maryland, College Park
Comments Graphics Seminar Series

Recent trends in parallel computer architecture strongly suggest the need to improve the arithmetic intensity (the compute to bandwidth ratio) for greater performance in time-critical applications, such as interactive 3D graphics. At the same time, advances in stream programming abstraction for graphics processors (GPUs) have enabled us to use parallel algorithm design methods for GPU programming. Inspired by these developments, this paper explores the interactions between multiple data streams to improve arithmetic intensity and address the input geometry bandwidth bottleneck for interactive 3D graphics applications.We introduce the idea of creating vertex and transformation streams that represent large point data sets via their interaction. We discuss how to factor such point datasets into a set of source vertices and transformation streams by identifying the most common translations amongst vertices. We accomplish this by identifying peaks in the cross-power spectrum of the dataset in the Fourier domain. We validate our approach by integrating it with a view-dependent point rendering system and show significant improvements in input geometry bandwidth requirements as well as rendering frame rates.

April 3, 2006  A Survey of Large High-Resolution Display Technologies, Techniques, and Applications
Presented By Greg Schmidt, Naval Research Lab
Comments Graphics Seminar Series

Continued advances in display hardware, computing power, networking, and rendering algorithms have all converged to dramatically improve large high-resolution display capabilities. We present a survey on prior research with large high-resolution displays. In the hardware configurations section we examine systems including multi-monitor workstations, reconfigurable projector arrays, and others. Rendering and the data pipeline are addressed with an overview of current technologies. We discuss many applications for large high-resolution displays such as automotive design, scientific visualization, control centers, and others. Quantifying the effects of large high-resolution displays on human performance and other aspects is important as we look toward future advances in display technology and how it is applied in different situations. Interacting with these displays brings a different set of challenges for HCI professionals, so an overview of some of this work is provided. Finally, we present our view of the top ten greatest challenges in large high-resolution displays.

March 27, 2006  Video Clips and Game Demos
Presented By Derek Juba, University of Maryland, College Park
Comments Graphics Seminar Series

The following clips and demos were shown: Outtakes from The Incredibles, the bonus short Jack-Jack Attack from The Incredibles, a demonstration of The Sims 2, and clips of Will Wright's GDC 2005 presentation of his new game, Spore.

March 13, 2006  How to Represent Non-Manifold Objects Efficiently
Presented By Annie Hui, University of Maryland, College Park
Comments Graphics Seminar Series

In solid-modeling, 3D shapes are often described indirectly by a subdivision of their boundary decomposition into elementary cells or triangles. Rarely are 3D shapes modeled as 3D meshes. This is because 3D meshes are difficult to generate. Moreover, it is hard to update a 3D mesh as the effects of a modification on such a mesh are not well studied.

In addition, most of existing geometric representations are for manifold shapes. Non-manifold shapes arise in several application contexts, often as the result of an abstraction process applied to manifold shapes. This happens, for instance, in the idealization process to which finite element meshes generated from CAD models undergo to meet simulation requirements. Most existing representations cannot handle non-manifold features, and some can handle such features at a high expense.

Therefore, the focus of my work has been on designing compact and powerful representations for non-manifold shapes of dimension 3 and above. In this talk, I would discuss a selection of existing works. Then I will present two representations that I have worked on. One is a highly compact data structure for representing non-manifold 3D shapes as a 3D mesh. The data structure is called the Non-manifold Indexed data structure with Adjacencies. Another is a dimenison-independent data structure, that we call the Incidence Simplicial data structure.

  Old Seminars








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