Rasmus Stenholt

Efficient selection of multiple objects on a large scale

The task of multiple object selection (MOS) in immersive virtual environments is important and still largely unexplored. The difficulty of efficient MOS increases with the number of objects to be selected. E.g. in small-scale MOS, only a few objects need to be simultaneously selected. This may be accomplished by serializing existing single-object selection techniques. In this paper, we explore various MOS tools for large-scale MOS. That is, when the number of objects to be selected are counted in hundreds, or even thousands. This makes serialization of single-object techniques prohibitively time consuming. Instead, we have implemented and tested two of the existing approaches to 3-D MOS, a brush and a lasso, as well as a new technique, a magic wand, which automatically selects objects based on local proximity to other objects. In a formal user evaluation, we have studied how the performance of the MOS tools are affected by the geometric configuration of the objects to be selected. Our studies demonstrate that the performance of MOS techniques is very significantly affected by the geometric scenario facing the user. Furthermore, we demonstrate that a good match between MOS tool shape and the geometric configuration is not always preferable, if the applied tool is complex to use.

Poster: Brush, lasso, or magic wand? Picking the right tool for large-scale multiple object selection tasks

Selection of multiple objects is a frequent interaction task in virtual environments. Accomplishing this task efficiently and intuitively is difficult, especially in cases where there are a very large number of objects to be selected. In this work, we seek to investigate two well-known techniques, a spherical brush and a box-shaped lasso for multiple object selection (MOS), and compare them to a new MOS technique, which we have named the magic wand. This new technique automates a lot the work, which the user would normally have to do manually. The comparison is made through a user study, where users are presented with a range of different geometric layouts of selection targets, to investigate the pros and cons of each of the MOS techniques. The evaluation shows that the magic wand is significantly faster to use than the other techniques, however the quality of the magic wands selections is highly dependent on the geometric scenario. The spherical brush proved to be a good overall technique, whereas the box lasso proved slow and inaccurate even in geometric scenarios specifically designed for the lasso.

Predictive Model for Group Selection Performance on Touch Devices

Users spend hours making selections with ineffective tools, we therefore examine selection methods for efficiency in various touch trials. In a preliminary study three alternative selection methods were identified, we compared these to a smart selection tool. The study showed that a single selection method was the fastest; however, when the amount of targets increased, a multiple selection tool became more efficient. A secondary study with more targets revealed similar results. We therefore examined the single selection method against traditional selection methods in a user study. The results reveal a model of the average action and time cost for all methods within the parameters of mental preparation and target addition. The study revealed that the most favored selection methods were a lasso and brush selection tool. The study provides evidence towards a predictive model of selection performance for multiple target selection trials.

On the Benefits of Using Constant Visual Angle Glyphs in Interactive Exploration of 3D Scatterplots

Visual exploration of clouds of data points is an important application of virtual environments. The common goal of this activity is to use the strengths of human perception to identify interesting structures in data, which are often not detected using traditional, computational analysis methods. In this article, we seek to identify some of the parameters that affect how well structures in visualized data clouds can be identified by a human observer. Two of the primary factors tested are the volumetric densities of the visualized structures and the presence/absence of clutter around the displayed structures. Furthermore, we introduce a new approach to glyph visualization—constant visual angle (CVA) glyphs—which has the potential to mitigate the effect of clutter at the cost of dispensing with the common real-world depth cue of relative size. In a controlled experiment where test subjects had to locate and select visualized structures in an immersive virtual environment, we identified several significant results. One result is that CVA glyphs ease perception of structures in cluttered environments while not deteriorating it when clutter is absent. Another is the existence of threshold densities, above which perception of structures becomes easier and more precise.

On the benefits of stereo graphics in virtual obstacle avoidance tasks

In virtual reality, stereo graphics is a very common way of increasing the level of perceptual realism in the visual part of the experience. However, stereo graphics comes at cost, both in technical terms and from a user perspective. In this paper, we present the preliminary results of an experiment to see if stereo makes any quantifiable, statistically significant difference in the ability to avoid collisions with virtual obstacles while navigating a 3-D space under constant acceleration. Our results indicate that for this particular application scenario, stereo does provide a significant benefit in terms of the amount of time that participants were able to avoid obstacles.

Shape perception in 3-D scatterplots using constant visual angle glyphs

When viewing 3-D scatterplots in immersive virtual environments, one commonly encountered problem is the presence of clutter, which obscures the view of any structures of interest in the visualization. In order to solve this problem, we propose to render the 3-D glyphs such that they always cover the the same amount of screen space. For perceptual reasons, we call this approach constant visual angle glyphs, or CVA glyphs. The use of CVA glyphs implies some desirable perceptual consequences, which have not been previously described or discussed in existing literature: CVA glyphs not only have the prospect of dealing with clutter, but also the prospect of allowing for a better perception of the continuous shapes of structures in 3-D scatterplots. In a formal user evaluation of CVA glyphs, the results indicate that such glyphs do allow for better perception of shapes in 3-D scatterplots compared to regular perspective glyphs, especially when a large amount of clutter is present. Furthermore, our evaluation revealed that perception of structures in 3-D scatterplots is significantly affected by the volumetric density of the glyphs in the plot.