Wednesday, October 24th, 2007
at 5:30PM

We present a novel approach for latency-tolerant delivery of visualization and rendering results where client-side frame rate display performance is independent of source dataset size, visualization technique or rendering complexity. Our approach delivers pre-rendered, multiresolution images to a remote user as they navigate through different viewpoints, visualization or rendering parameters. We employ demand-driven tiled, multiresolution image streaming and prefetching to efficiently utilize available bandwidth while providing the maximum resolution user can perceive from a given viewpoint. Since image data is the only input to our system, our approach is generally applicable to all visualization and graphics rendering applications capable of generating image files in an ordered fashion. In our implementation, a normal web server provides on-demand images to a remote custom client application, which uses client-pull to obtain and cache only those images required to fulfill the interaction needs. The main contributions of this work are: (1) an architecture for latency-tolerant, remote delivery of precomputed imagery suitable for use with any visualization or rendering application capable of producing images in an ordered fashion; (2) a performance study showing the impact of diverse network environments and different tunable system parameters on end-to-end system performance in terms of deliverable frames per second.

Dr. Ilmi Yoon is an Associate Professor in the Computer Science Department of San Francisco State University. She earned both her MS and Ph.D. degrees in Computer Science at the University of Southern California at Los Angeles in 1996 and 2000. Her focus was on "Web-based Remote Rendering using Image- Based Rendering Techniques." Her recent research focuses on 3D network visualizations on the WWW, 3D Visualizations related to Life Science, and Serious Games for Nursing. Her research relates to interactive media, Web3D, and Information Visualization.