Complementary space for enhanced uncertainty and dynamics visualization

Many computational modeling pipelines for geometry processing and visualization focus on topologically and geometrically accurate shape reconstruction of “primal” space, meaning the surface of interest and the volume it contains. Certain features of a surface such as pockets, tunnels, and voids (small, closed components) often represent important properties of the model and yet are difficult to detect or visualize in a model of primal space alone. It is natural, then, to consider what information can be gained from a model and visualization of complementary space, i.e. the space exterior to but still “near” the surface in question. In this paper, we show how complementary space can be used as a tool for both uncertainty and dynamics visualizations and analysis.