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This work presents, via an in-depth case study on how parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, environmental data sets. Advanced visual interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading are combined into an interactive geovisual analytics system. Moreover, the system facilitates statistical processes such as stepwise regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. Using a systematic workflow, this approach is demonstrated via a North Atlantic hurricane climate study in close collaboration with a domain expert. By revealing several important physical associations, the case study confirms that the visual analytics approach facilitates a deeper understanding of multidimensional climate data sets when compared to traditional techniques., Introduction One of the most challenging tasks in multivariate data analysis is to identify and quantify the associations between a set of interrelated variables. In climate studies, this task is [...]

Does visually perceived distance differ when objects are viewed in augmented reality (AR), as opposed to the real world? What are the differences? These questions are theoretically interesting, and the answers are important for the development of many tablet- and phone-based AR applications, including mobile AR navigation systems. This article presents a thorough literature review of distance judgment experimental protocols, and results from several areas of perceptual psychology. In addition to distance judgments of real and virtual objects, this section also discusses previous work in measuring the geometry of virtual picture space and considers how this work might be relevant to tablet AR. Then, the article presents the results of two experiments. In each experiment, observers bisected egocentric distances of 15 and 30 m in tablet-based AR and in the real world, in both indoor corridor and outdoor field environments. In AR, observers bisected the distances to virtual humans, while in the real world, they bisected the distances to real humans. This is the first reported research that directly compares distance judgments of real and virtual objects in a tablet AR system. Four key findings were: (1) In AR, observers expanded midpoint intervals at 15 m, but compressed midpoints at 30 m. (2) Observers were accurate in the real world. (3) The environmental setting—corridor or open field—had no effect. (4) The picture perception literature is important in understanding how distances are likely judged in tablet-based AR. Taken together, these findings suggest the depth distortions that AR application developers should expect with mobile and especially tablet-based AR. [ABSTRACT FROM AUTHOR]

We present the results from a user study looking at the ability of observers to mentally integrate wind direction and magnitude over a vector field. The data set chosen for the study is an MM5 (PSU/NCAR Mesoscale Model) simulation of Hurricane Lili over the Gulf of Mexico as it approaches the southeastern United States. Nine observers participated in the study. This study investigates the effect of layering on the observer's ability to determine the magnitude and direction of a vector field. We found a tendency for observers to underestimate the magnitude of the vectors and a counter-clockwise bias when determining the average direction of a vector field. We completed an additional study with two observers to try to uncover the source of the counter-clockwise bias. These results have direct implications to atmospheric scientists, but may also be able to be applied to other fields that use 2D vector fields. [ABSTRACT FROM AUTHOR]

A major challenge, and thus opportunity, in the field of human-computer interaction and specifically usability engineering (UE) is designing effective user interfaces for emerging technologies that have no established design guidelines or interaction metaphors or introduce completely new ways for users to perceive and interact with technology and the world around them. Clearly, augmented reality (AR) is one such emerging technology. We propose a UE approach that employs user-based studies to inform design by iteratively inserting a series of user-based studies into a traditional usability-engineering life cycle to better inform initial user interface designs. We present an exemplar user-based study conducted to gain insight into how users perceive text in outdoor AR settings and to derive implications for design in outdoor AR. We also describe "lessons learned" from our experiences, conducting user-based studies as part of the design process. [ABSTRACT FROM AUTHOR]

A fundamental problem in optical, see-through augmented reality (AR) is characterizing how it affects the perception of spatial layout and depth. This problem is important because AR system developers need to both place graphics in arbitrary spatial relationships with real-world objects, and to know that users will perceive them in the same relationships. Furthermore, AR makes possible enhanced perceptual techniques that have no real-world equivalent, such as x-ray vision, where AR users are supposed to perceive graphics as being located behind opaque surfaces. This paper reviews and discusses protocols for measuring egocentric depth judgments in both virtual and augmented environments, and discusses the well-known problem of depth underestimation in virtual environments. It then describes two experiments that measured egocentric depth judgments in AR. Experiment I used a perceptual matching protocol to measure AR depth judgments at medium and far-field distances of 5 to 45 meters. The experiment studied the effects of upper versus lower visual field location, the x-ray vision condition, and practice on the task. The experimental findings include evidence for a switch in bias, from underestimating to overestimating the distance of AR-presented graphics, at ∼ 23 meters, as well as a quantification of how much more difficult the x-ray vision condition makes the task. Experiment II used blind walking and verbal report protocols to measure AR depth judgments at distances of 3 to 7 meters. The experiment examined real-world objects, real-world objects seen through the AR display, virtual objects, and combined real and virtual objects. The results give evidence that the egocentric depth of AR objects is underestimated at these distances, but to a lesser degree than has previously been found for most virtual reality environments. The results are consistent with previous studies that have implicated a restricted field-of-view, combined with an inability for observers to scan the ground plane in a near-to-far direction, as explanations for the observed depth underestimation. [ABSTRACT FROM AUTHOR]

A challenge in presenting augmenting information in outdoor augmented reality (AR) settings lies in the broad range of uncontrollable environmental conditions that may be present, specifically large-scale fluctuations in natural lighting and wide variations in likely backgrounds or objects in the scene. In this paper, we motivate the need for research on the effects of text drawing styles, outdoor background textures, and natural lighting on user performance in outdoor AR. We present a pilot study and a follow-on user-based study that examined the effects on user performance of outdoor background textures, changing outdoor illuminance values, and text drawing styles in a text identification task using an optical, see-through AR system. We report significant effects for all these variables, and discuss user interface design guidelines and ideas for future work. [ABSTRACT FROM AUTHOR]

This paper presents a 2D flow visualization user study that we conducted using new methodologies to increase the objectiveness. We evaluated grid-based variable-size arrows, evenly spaced streamlines, and line integral convolution (LIC) variants (basic, oriented, and enhanced versions) coupled with a colorwheel and/or rainbow color map, which are representative of many geometry-based and texture-based techniques. To reduce data-related bias, template-based explicit flow synthesis was used to create a wide variety of symmetric flows with similar topological complexity. To suppress task-related bias, pattern-based implicit task design was employed, addressing critical point recognition, critical point classification, and symmetric pattern categorization. In addition, variable-duration and fixed-duration measurement schemes were utilized for lightweight precision-critical and heavyweight judgment-intensive flow analysis tasks, respectively, to record visualization effectiveness. We eliminated outliers and used the Ryan REGWQ post-hoc homogeneous subset tests in statistical analysis to obtain reliable findings. Our study shows that a texture-based dense representation with accentuated flow streaks, such as enhanced LIC, enables intuitive perception of the flow, while a geometry-based integral representation with uniform density control, such as evenly spaced streamlines, may exploit visual interpolation to facilitate mental reconstruction of the flow. It is also shown that inappropriate color mapping (e.g., colorwheel) may add distractions to a flow representation. [ABSTRACT FROM AUTHOR]