Limited resource visualization with region-of-interest

Abstract

This thesis studies some issues on applying region-of-interest in visualization. In visualization, a critical consideration is on how to handle very large data-set with limited resources, specifically computational resources and display window size. Region-of-interest (ROI) technique can be employed as a potential solution to serve the following two purposes: 1) It allocates more computational resources to the interesting region. 2) It assists the viewer by filtering out less interesting information. In this thesis, we study the above issues in the context of two applications: remote volume visualization with limited computational resources at the client side, and vector map visualization in small display window. For the first application, a technical issue is on how to apply ROI on volume visualization efficiently. This is important in scenarios where the viewer has access to low computational resources. Another issue is on how to apply ROI effectively. We give several methods to adjust the transfer function to highlight objects in the ROI. For the second application, consideration should be given on how to present the local and global geographic information simultaneously in the limited display window. We give a map generalization method that first adopts fisheye view to exaggerate information in ROI followed by a line smoothing process to eliminate the clutter caused by the distortion. The smoothing process is essentially an iteration of localized smoothing processes that maintain the topological consistency.