Dataflow and Remapping for Wavelet Compression and View-dependent Optimization of Billion-triangle Isosurfaces

Currently, large physics simulations produce 3D discretized field data whose individual isosurfaces, after conventional extraction processes, contain upwards of hundreds of millions of triangles. Detailed interactive viewing of these surfaces requires (a) powerful compression to minimize storage, and (b) fast view-dependent optimization of display triangulations to most effectively utilize high-performance graphics hardware. In this work, we introduce the first end-to-end multiresolution data flow strategy that can eectively combine the top performing subdivision-surface wavelet compression and view-dependent optimization methods, thus increasing efficiency by several orders of magnitude over conventional processing pipelines. In addition to the general development and analysis of the data ow, we present new algorithms at two steps in the pipeline that provide the "glue" that makes an integrated large-scale data visualization approach possible. A shrink-wrapping step converts highly detailed unstructured surfaces of arbitrary topology to the semi-structured meshes needed for wavelet compression. Remapping to triangle bintrees minimizes disturbing "pops" during realtime display-triangulation optimization and provides eective selective-transmission compres-ion for out-of-core and remote access to extremely large surfaces. Overall, this is the first effort to exploit semi-structured surface representations for a complete large-data visualization pipeline

Real-Time Adaptive Human Motions for Web-Based Training

4th International Conference on Web-Based Learning, Hong Kong, China, July 31 - August 3, 2005Web-based training offers many benefits over instructor-led training environments. It provides a time, class size and geographical location independent learning platform to students. To enable active learning and enhance the effectiveness in students’ understanding of the training materials, multimedia cues, like 3D graphics, animation and sound, have been employed in web-based training systems to achieve these goals. However, if a training system involves a large amount of 3D animation, such as crowd animation in an emergency evacuation training system, the requirements for rendering capability and network bandwidth may become too high to meet. In this paper, we propose an adaptive human motion animation method to support real-time rendering and transmission of human motions in web-based training systems. Our method offers a mechanism to extract human motion data at various levels of detail (LoD). We also propose a set of importance factors to allow a web-based training system to determine the LoD of the human motion for rendering as well as the LoD for transmission, according to the importance of the motion and the available network bandwidth, respectively. We demonstrate the effectiveness of the new method with some experimental results.Department of ComputingRefereed conference pape