Building perceptual textures to visualize multidimensional datasets

摘要: Presents a new method for using texture to visualize multi-dimensional data elements arranged on an underlying 3D height field. We hope use simple patterns in combination with other visual features like hue and intensity increase the number of attribute values we can display simultaneously. Our technique builds perceptual (or pexels) represent each element. Attribute encoded element are used vary appearance corresponding pexel. Texture that form when pexels displayed be rapidly accurately explore dataset. built by controlling three separate dimensions: height, density regularity. Results from computer graphics, vision cognitive psychology have identified these dimensions as important formation patterns. conducted set controlled experiments measure effectiveness dimensions, identify any interference may occur all simultaneously at same spatial location. our show specific combinations textures visualizing multidimensional datasets. demonstrate applying it two real-world visualization environments: tracking typhoon activity southeast Asia, analyzing ocean conditions northern Pacific.