This project investigates new methods to efficiently render volumetric data based on the region of interests.
The contour tree is a topological abstraction of a scalar ﬁeld. It represents the nesting relationships of connected components of isosurfaces or contours. The real-world data sets produce unmanageably large contour trees because of noise and artifacts. This renders the contour tree impractical for data analysis and visualization. A meaningful simpliﬁcation is necessary to the contour tree.
This project investigates an importance-driven approach which combines different measures of importance into a single contour tree simpliﬁcation pipeline through an importance triangle (ITri). The ITri is set up based on the importance measure vector, whose components are different measures of importance. Through the interaction interfaces, the user can specify models for combining different measures of importance into the contour tree simpliﬁcation pipeline.
The opportunity ID for this research opportunity is 389