N. Touheed, P. Selwood, P.K. Jimack, M. Berzins. A Comparison of Some Dynamic Load Balancing Algorithms for a Parallel Adaptive Flow Solver, In Parallel Computing, Vol. 26, No. 12, pp. 1535--1554. 2000.
X. Tricoche, G. Scheuermann, H. Hagen. Higher Order Singularities in Piecewise Linear Vector Fields, In The Mathematics of Surfaces IX, Springer, London, pp. 99--113. 2000.
X. Tricoche, G. Scheuermann, H. Hagen. A Topology Simplification Method for 2D Vector Fields, In Proceedings of IEEE Visualization 2000, pp. 359--366. 2000.
D.C. Van Essen, H.A. Drury, S. Joshi, M. Miller. Functional and Structural Mapping of Human Cerebral Cortex: Solutions are in the Surfaces, In Adv Neurol, Vol. 84, pp. 23--34. 2000.
D.M. Weinstein, L. Zhukov, G. Potts. Localization of Multiple Deep Epileptic Sources in a Realistic Head Model via Independent Component Analysis, School of Computing Technical Report, No. UUCS-2000-004, University of Utah, February, 2000.
D.M. Weinstein, L. Zhukov, C.R. Johnson. Lead-Field Bases for EEG Source Imaging, In Annal. Biomed. Eng., Vol. 28, No. 9, pp. 1059--1065. Sep, 2000.
D. Weinstein. Scanline Surfacing: Building Separating Surfaces from Planar Contours, In Proceeding of IEEE Visualization 2000, pp. 283--289. 2000.
D.M. Weinstein, L. Zhukov, C.R. Johnson. An Inverse EEG Problem Solving Environment and its Applications to EEG Source Localization, In NeuroImage (suppl.), pp. 921. 2000.
M. Weiler, R. Westermann, C.D. Hansen, K. Zimmerman, T. Ertl. Level-Of-Detail Volume Rendering via 3D Textures, In Proceeding of IEEE Volume Visualization 2000, SLC, Utah, pp. 7--13. October, 2000.
D.M. Weinstein, L. Zhukov, C.R. Johnson, S.G. Parker, R. Van Uitert, R.S. MacLeod, C.D. Hansen. Interactive Source Imaging with BioPSE, In Chicago 2000 World Congress on Medical Physics and Biomedical Engineering, Chicago, IL., Note: Refereed abstract., July, 2000.
D.M. Weinstein, P. Krysl, C.R. Johnson. The BioPSE Inverse EEG Modeling Pipeline, In ISGG 7th International Conference on Numerical Grid Generation in Computation Field Simulations, The International Society of Grid Generation, Mississippi State University pp. 1091--1100. 2000.
R. Westermann, C.R. Johnson, T. Ertl. A Level-Set Method for Flow Visualization, In Proceeding of IEEE Visualization 2000, IEEE Computer Society, Salt Lake City pp. 147--154. 2000.
L. Zhukov, D. Weinstein, C.R. Johnson. Statistical Analysis For FEM EEG Source Localization in Realistic Head Models, School of Computing Technical Report, No. UUCS-2000-003, University of Utah, February, 2000.
L. Zhukov, D.M. Weinstein, C.R. Johnson. Reciprocity Basis for EEG Source Imaging, In NeuroImage (suppl.), pp. 598. 2000.
L. Zhukov, D. Weinstein, C.R. Johnson. Independent Component Analysis for EEG Source Localization in Realistic Head Models, In IEEE Engineering in Medicine and Biology, Vol. 19, No. 3, pp. 87--96. 2000.
R. Armstrong, D. Gannon, A. Geist, K. Keahey, S. Kohn, L. McInnes, S.G. Parker, B. Smolinksi. Toward a Common Component Architecture for High-Performance Scientific Computing, In Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computation (HPDC), August, 1999.
C.L. Bajaj, C. Baldazzi, S. Cutchin, A. Paoluzzi, V. Pascucci, M. Vicentino. A Programming Approach for Complex Animations, In Computer Aided Design, Vol. 31, No. 11, pp. 695--710. 1999.
C.L. Bajaj, V. Pascucci, G. Zhuang.
Single Resolution Compression of Arbitrary Triangular Meshes with Properties, In Computational Geometry: Theory and Applications, Vol. 14, No. 1--3, pp. 167--186. 1999.
Triangular meshes are widely used as primary representation of surface models for networked gaming and for complex interactive design in manufacturing. Accurate triangulation of a surface with sharp features (highly varying curvatures, holes) may require an extremely large number of triangles. Fast transmission of such large triangle meshes is critical to many applications that interactively manipulate geometric models in remote networked environments. The need for a succinct representation is therefore not only to reduce static storage requirements, but also to consume less network bandwidth and thus reduce the transmission time.
In this paper we address the problem of defining a space efficient encoding scheme for both lossless and error-bounded lossy compression of triangular meshes that is robust enough to handle directly arbitrary sets of triangles including non-orientable meshes, non-manifold meshes and even non-mesh cases. The compression is achieved by capturing the redundant information in both the topology (connectivity) and geometry with possibly property attributes. Example models and results are also reported.
C.L. Bajaj, V. Pascucci, D.R. Schikore. Data Visualization Techniques, Trends in Software, Vol. 6, Ch. 3: Accelerated IsoContouring of Scalar Fields, John Wiley & Sons, pp. 31--47. 1999.