Abstract
Abstract. Tasks such as image registration or pose estimation require the determination of transformations based on uncertain observations. Hence, the position of any geometric object transformed according to this estimate is also uncertain, at least in terms of precision. Often the knowledge of uncertainty changes the judgment of individuals. Thus, the visualization of this information is crucial whenever a human decision-maker is involved. In the absence of error-free reference data, we consider the estimated precision as the probably most important quantity characterizing the uncertainty. This contribution focuses on the visualization of positional precision as provided by estimated covariance matrices. Basic design principles such as coloration and contouring in 2D and 3D are presented and discussed in the context of practical applications, e.g., the superimposition of distance information as seen nowadays in sports broadcasts. As a novel contribution, we propose quartic plane curves to represent the confidence regions of the loci of conic sections.
Highlights
1.1 Motivation“One of the most challenging aspects of data visualization is the visualization of uncertainty
When we see a data point drawn in a specific location, we tend to interpret it as a precise representation of the true data value
A sophisticated visualization of uncertainty is crucial in many practical applications with the participation of human decision-makers
Summary
“One of the most challenging aspects of data visualization is the visualization of uncertainty. It is difficult to conceive that a data point could lie somewhere it hasn’t been drawn.” (Wilke, 2019). This observation motivates the quantification and visualization of positional uncertainty in this contribution: Sampled spatial data often features unknown positional errors, resulting in the question of where a data point or an object should be displayed. A sophisticated visualization of uncertainty is crucial in many practical applications with the participation of human decision-makers. As it is generally known, the inclusion of information about uncertainty changes the judgment of individuals. The challenge is to transform quantified positional uncertainty into a visualization that enables clear perception
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
