M. Ewert

Bio: M. Ewert is an academic researcher from University of Minnesota. The author has contributed to research in topics: Animation. The author has an hindex of 1, co-authored 1 publications receiving 13 citations.

Visualizing Motion Data in Virtual Reality: Understanding the Roles of Animation, Interaction, and Static Presentation

Abstract: We present a study of interactive virtual reality visualizations of scientific motions as found in biomechanics experiments. Our approach is threefold. First, we define a taxonomy of motion visualizations organized by the method (animation, interaction, or static presentation) used to depict both the spatial and temporal dimensions of the data. Second, we design and implement a set of eight example visualizations suggested by the taxonomy and evaluate their utility in a quantitative user study. Third, together with biomechanics collaborators, we conduct a qualitative evaluation of the eight example visualizations applied to a current study of human spinal kinematics. Results suggest that visualizations in this style that use interactive control for the time dimension of the data are preferable to others. Within this category, quantitative results support the utility of both animated and interactive depictions for space; however, qualitative feedback suggest that animated depictions for space should be avoided in biomechanics applications. © 2012 Wiley Periodicals, Inc.

Considerations for Visualizing Comparison

Abstract: Supporting comparison is a common and diverse challenge in visualization. Such support is difficult to design because solutions must address both the specifics of their scenario as well as the general issues of comparison. This paper aids designers by providing a strategy for considering those general issues. It presents four considerations that abstract comparison. These considerations identify issues and categorize solutions in a domain independent manner. The first considers how the common elements of comparison—a target set of items that are related and an action the user wants to perform on that relationship—are present in an analysis problem. The second considers why these elements lead to challenges because of their scale, in number of items, complexity of items, or complexity of relationship. The third considers what strategies address the identified scaling challenges, grouping solutions into three broad categories. The fourth considers which visual designs map to these strategies to provide solutions for a comparison analysis problem. In sequence, these considerations provide a process for developers to consider support for comparison in the design of visualization tools. Case studies show how these considerations can help in the design and evaluation of visualization solutions for comparison problems.

An Evaluation of Depth Enhancing Perceptual Cues for Vascular Volume Visualization in Neurosurgery

Abstract: Cerebral vascular images obtained through angiography are used by neurosurgeons for diagnosis, surgical planning, and intraoperative guidance. The intricate branching of the vessels and furcations, however, make the task of understanding the spatial three-dimensional layout of these images challenging. In this paper, we present empirical studies on the effect of different perceptual cues (fog, pseudo-chromadepth, kinetic depth, and depicting edges) both individually and in combination on the depth perception of cerebral vascular volumes and compare these to the cue of stereopsis. Two experiments with novices and one experiment with experts were performed. The results with novices showed that the pseudo-chromadepth and fog cues were stronger cues than that of stereopsis. Furthermore, the addition of the stereopsis cue to the other cues did not improve relative depth perception in cerebral vascular volumes. In contrast to novices, the experts also performed well with the edge cue. In terms of both novice and expert subjects, pseudo-chromadepth and fog allow for the best relative depth perception. By using such cues to improve depth perception of cerebral vasculature, we may improve diagnosis, surgical planning, and intraoperative guidance.

A Survey of Flattening‐Based Medical Visualization Techniques

Abstract: In many areas of medicine, visualization research can help with task simplification, abstraction or complexity reduction. A common visualization approach is to facilitate parameterization technique ...

Comparison techniques utilized in spatial 3D and 4D data visualizations: A survey and future directions

Abstract: A variety of visualization techniques can be utilized to compare multiple Spatial 3D or time-varying Spatial 3D data instances (e.g., comparing pre- versus post-treatment volumetric medical images). However, despite the fact that comparative visualization is frequently needed – scientists, engineers, and even humanists must routinely compare such data – visualization users and practitioners suffer from a lack of adequate Spatial 3D comparative visualization tools and guidelines. Here we survey the field and present a taxonomy for classifying existing and new comparison visualization techniques for such data into four fundamental approaches: Juxtaposition, Superimposition, Interchangeable, and Explicit Encoding. The results clarify the key design decisions and tradeoffs that designers must make to create an effective comparative Spatial 3D data visualization and suggest the potential of emerging hybrid approaches, ones creatively combining aspects of the four fundamental approaches.

Immersive analysis of user motion in VR applications

Abstract: With the rise of virtual reality experiences for applications in entertainment, industry, science and medicine, the evaluation of human motion in immersive environments is becoming more important. By analysing the motion of virtual reality users, design choices and training progress in the virtual environment can be understood and improved. Since the motion is captured in a virtual environment, performing the analysis in the same environment provides a valuable context and guidance for the analysis. We have created a visual analysis system that is designed for immersive visualisation and exploration of human motion data. By combining suitable data mining algorithms with immersive visualisation techniques, we facilitate the reasoning and understanding of the underlying motion. We apply and evaluate this novel approach on a relevant VR application domain to identify and interpret motion patterns in a meaningful way.