Time-varying data is usually explored by animation or arrays of static images. Neither is particularly effective for classifying data by different temporal activities. Important temporal trends can be missed due to the lack of ability to find them with current visualization methods. In this paper, we propose a method to explore data at different temporal resolutions to discover and highlight data based upon ...


















Inspired by the abstracting, focusing and explanatory qualities of diagram drawing in art, in this paper we propose a novel seeding strategy to generate representative and illustrative streamlines in 2D vector fields to enforce visual clarity and evidence. A particular focus of our algorithm is to depict the underlying flow patterns effectively and succinctly with a minimum set of streamlines. To achieve this goal, ...


















We present a technique for memory-efficient and time-efficient volume rendering of curvilinear adaptive mesh refinement data defined within extrudable computational spaces. One of the main challenges in the ray casting of curvilinear volumes is that a linear viewing ray in physical space will typically correspond to a curved ray in computational space. The proposed ...


















We present a non-photorealistic rendering technique for interactive exploration of isosurfaces generated from remote volumetric data. Instead of relying on the conventional smooth shading technique to render the isosurfaces, a point-based technique is used to represent and render the isosurfaces in a remote client-server environment. The non-photorealistic nature of the ...








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The Ohio State University, Department of Computer Science and Engineering

395 Dreese Lab, 2015 Neil Avenue, Columbus OH 43210

Professor Han-Wei Shen

hwshen@cse.ohio-state.edu (V) 614 292 0060  (F) 614 2922911