Point-based probabilistic surfaces to show surface uncertainty

Abstract

Efficient and informative visualization of surfaces with uncertainties is an important topic with many applications in science and engineering. In these applications, the correct course of action may depend not only on the location of a boundary, but on the precision with which that location is known. Examples include environmental pollution borderline detection, oil basin edge characterization, or discrimination between cancerous and healthy tissue in medicine. This paper presents a method for producing visualizations of surfaces with uncertainties using points as display primitives. Our approach is to render the surface as a collection of points and to displace each point from its original location along the surface normal by an amount proportional to the uncertainty at that point. This approaoh can be used in combination with other techniques such as pseudocoloring to produce efficient and revealing visualizations. The basic approach is sufficiently flexible to allow natural extensions; we show incorporation of expressive modulation of opacity, change of the stroke primitive, and addition of an underlying polygonal model. The method is used to visualize real and simulated tumor formations with uncertainty of tumor boundaries. The point-based technique is compared to pseudocoloring for a position estimation task in a preliminary user study.

How to Assess Visual Communication of Uncertainty? A Systematic Review of Geospatial Uncertainty Visualisation User Studies

“…Edwards and Nelson (2001) found that bivariate symbols depicting data and uncertainty (size combined with either focus or colour value) yielded higher confidence (along with more accurate results) than verbal and graphical depiction of uncertainty in the legend. Grigoryan and Rheingans (2004) suggested significantly higher confidence (as well as higher accuracy and shorter response times) when a point-based representation of positional uncertainty was used, compared to colour coding. Kolbeinsson (2013) reported higher confidence for shape changes than for icon degradation that also corresponded to higher response accuracy.…”

“…In the static 3D displays they used, these techniques outperformed intrinsic techniques such as colour mapping, transparency and aliasing (a combination of transparency and blur). In related research, Grigoryan and Rheingans (2004) found that with a spatial task in a 3D display (tell if a marker is inside of the error margin of a surface), subjects were significantly more accurate and faster when the error margin was represented by points than with pseudo-colouring of the surface. In the above mentioned study by Sanyal et al (2009) subjects performed well with two kinds of spherical glyphs (varying size and colour value) in a 2D and a 3D display.…”

“…variance) of statistical data (MacEachren et al, 1998). Just one study (at least from those focusing on communication of uncertainty) deals with positional uncertainty visualisation exclusively (Grigoryan and Rheingans, 2004). There are no studies in the set assembled here that solely deal with temporal aspects of uncertainty.…”

“…For instance, this is used to assess the confidence with a response (Alberti, 2013;Blenkinsop et al, 2000;Edwards and Nelson, 2001;Evans, 1997;Grigoryan and Rheingans, 2004;Kolbeinsson, 2013;Kubíček and Šašinka, 2011;Leitner and Buttenfield, 2000). Other studies determine the users' preference for a certain technique (Boukhelifa et al, 2012;Gerharz and Pebesma, 2009;Kardos et al, 2003;Retchless, 2012;Senaratne et al, 2012), assessment about ease-of-use of a map or visualisation (Grigoryan and Rheingans, 2004;MacEachren et al, 1998) or judgment of map attractiveness (MacEachren et al, 1998). Subjective assessment is also used to determine or the intuitiveness of different symbols (MacEachren et al, 2012), the difficulty to identify data and uncertainty (Newman and Lee, 2004), or the degree of visual overload (Newman and Lee, 2004) perceived by participants.…”

Uncertainty in the Development and Use of Equation of State Models

“…The first prototype implements a technique presented in [5] that renders a cloud of three dimensional points at a variable distance normal to a surface. The emphasis of this prototype is to show uncertainty in the exact location of the surface.…”