Evaluation of Memoryless Simplification
IEEE Transactions on Visualization and Computer Graphics
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Visibility Culling for Time-Varying Volume Rendering Using Temporal Occlusion Coherence
VIS '04 Proceedings of the conference on Visualization '04
Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
IV '05 Proceedings of the Ninth International Conference on Information Visualisation
Progressive Volume Rendering of Large Unstructured Grids
IEEE Transactions on Visualization and Computer Graphics
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This paper presents a new technique for selecting proper objects for accelerating visualization of large datasets similar to urban areas. The proposed method improves the current algorithms by introducing a new technique which uses statistics about different objects to cover more general and comprehensive datasets. In this technique, proximity, level of details, and statistics from previous moves are used to predict next position and to select objects for future use. A multi-resolution approach is introduced which is based on a special shape. By gathering statistics about different objects a unique shape called layer is obtained that is used to select different objects and put them in the groups to be rendered with different resolutions. This way acceleration to produce high resolution visualization at interactive rate is achieved. The proposed technique solves the issues of redundant object downloading and redundant rendering on the server by downloading objects and images based on software and hardware specifications. This way it saves server and network resources to reduce the delay and to achieve interactive frame rate on client side.