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Author Mishchenko, Oleg ♦ Crawfis, Roger
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Dimensional Flow ♦ Three Dimensional Flow Visualization ♦ Effective Texture Model ♦ User Study ♦ High Scoring Texture ♦ Flow Visualization ♦ Candidate Texture ♦ Inevitable Clutter ♦ Critical Point ♦ Discretized Domain ♦ Several Pixel ♦ Specific Guideline ♦ Visualization Blurry ♦ Geometry Primitive ♦ Different Depth ♦ Geometric Primitive ♦ Linear Flow ♦ Perceptual Limit ♦ Adequate Model ♦ Perform Well ♦ Textured Line ♦ Flow Direction ♦ Streamline Texture Model ♦ Local Neighborhood ♦ Dimensional Flow Visualization ♦ Total Number ♦ Effective Visualization ♦ Parameter Space ♦ Small Neighborhood ♦ Semi-transparent Geometry ♦ Experimental Dataset ♦ Many Different Flow Direction ♦ Screen Space ♦ General Texture Model ♦ Create Animation ♦ Quantitative Guideline
Abstract Visualizing three dimensional flow with geometry primitives is challenging due to inevitable clutter and occlusion. Our approach to tackling this problem is to utilize semi-transparent geometry as well as animation. Using semi-transparency, however, can make the visualization blurry and vague. We investigate perceptual limits and find specific guidelines on using semi-transparency for three dimensional flow visualization. We base our results on the user study that we conducted. The users were shown multiple semi-transparent overlapping layers of flow and were asked how many different flow directions they were able to discern. We utilized textured lines as geometric primitives; two general texture models were used to control opacity and create animation. We found that the number of high scoring textures is small compared to the total number of textures within our models. To test our findings, we utilized the high scoring textures to create visualizations of a variety of datasets. dataset. This model was selected for two reasons. First, we assume that textures that do not work well for 2.5D flow visualization, won’t perform well for three dimensional flow. Second, we observe the following: for any sufficiently small neighborhood in screen space, we can assume that the projection of three dimensional flow to this neighborhood consists of a number of overlapping linear flows at different depths. The only exception are vicinities of critical points. However, as we are dealing with a discretized domain, for a local neighborhood with a size of several pixels, we get one flow direction at this location at a given depth. Thus, our experimental dataset is an adequate model for the purposes of our study, which is primarily focused on occlusion. We explore the parameter space of streamline texture models and discard those textures that do not create effective visualizations. We select a set of candidate textures for our user study. The results of the user study provide us with qualitative and quantitative guidelines on using semitransparency for flow visualization to mitigate occlusion. 1
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study