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Stipple Rendering for Fast Volume Exploration

Alark Joshi and Penny Rheingans


Illustrations are an effective means for communicating and sharing ideas. They are successful at effectively drawing our attention to a region of interest, at the same time abstracting out irrelevant details. Visualizing large data is intrinsically a complex task that deals with understanding the spatial relationships within the dataset. Illustration-inspired techniques can greatly help a domain expert explore their data to get an improved understanding of their data. Due to the inherent abstraction in illustrative visualization, the simplified representation of the data increases the efficiency of the rendering algorithm. We use an illustration-inspired technique based on stippling to facilitate the exploration of large volumetric datasets. We vary stipple density, size and variability of the stipples to convey the undergone magnitude of change, by drawing attention to features in the data.