Semantics by analogy for illustrative volume visualization

Abstract

We present an interactive graphical approach for the explicit specification of semantics for volume visualization. This explicit and graphical specification of semantics for volumetric features allows us to visually assign meaning to both input and output parameters of the visualization mapping. This is in contrast to the implicit way of specifying semantics using transfer functions. In particular, we demonstrate how to realize a dynamic specification of semantics which allows to flexibly explore a wide range of mappings. Our approach is based on three concepts. First, we use semantic shader augmentation to automatically add rule-based rendering functionality to static visualization mappings in a shader program, while preserving the visual abstraction that the initial shader encodes. With this technique we extend recent developments that define a mapping between data attributes and visual attributes with rules, which are evaluated using fuzzy logic. Second, we let users define the semantics by analogy through brushing on renderings of the data attributes of interest. Third, the rules are specified graphically in an interface that provides visual clues for potential modifications. Together, the presented methods offer a high degree of freedom in the specification and exploration of rule-based mappings and avoid the limitations of a linguistic rule formulation.

Automatic suggestions to improve the quality of scatterplots during its creation

“…Additionally, semantic specifications for particular visualization aspects such as the user domain data classification, the visual representation, and the visual mapping were developed. Some examples include size-based data classifications [24,25], a taxonomy for visualization algorithms that was based on assumptions over their inputs [26], the characterization of visual variables to represent visual representations at a higher level of abstraction [27], the use of fuzzy logic semantics to replace the traditional transfer function setup in illustrative volume rendering [28,29], and a specific semantic model created by a machine learning mechanism that used representative dataset collections as training sets [30].…”

Smart Surrogate Widgets for Direct Volume Manipulation

“…Guo et al [11] developed a sketch-based approach for volume rendering manipulation, allowing for quick and easy adjustment of properties such as such as color, transparency, contrast, or brightness. Gerl et al [10] proposed an interactive approach for the explicit specification of semantics in volume visualization, to visually assign meaning to both input and output parameters of the visualization mapping.…”

Interactive Illustrative Line Styles and Line Style Transfer Functions for Flow Visualization

“…The first is halos [ARS79, SGS05, TCM06, EBRI09] that make objects (including lines) easier to discern from the background, thus improving depth perception. The second is the use of transfer functions, well known from volume rendering [KKH02], to display multiple styles in one visualization, e. g., as used for volumetric style transfer functions [BG07,GRIG12]. In the context of flow visualization [BCP * 12], other illustrative methods related to our work include stroke-and painting-inspired visualizations of 2D flow fields [KML99, LHS08], illustrative 3D volume rendering [SJEG05], stylized streamlines [MTHG03,LS07,LGP12], textured streamlines [JZDL07], animated, dashed streamlines [LH05] and dashtubes [FG98], as well as illustrative stream ribbons and surfaces [BWF * 10, HGH * 10, CYY * 11].…”