Abstract
Analysis of raw volume data generated from different scanning technologies faces a variety of challenges, related to search, pattern recognition, spatial understanding, quantitative estimation, and shape description. In a previous study, we found that the Volume Cracker (VC) 3D interaction (3DI) technique mitigated some of these problems, but this result was from a tethered glove-based system with users analyzing simulated data. Here, we redesigned the VC by using untethered bare-hand interaction with real volume datasets, with a broader aim of adoption of this technique in research labs. We developed symmetric and asymmetric interfaces for the Bare-Hand Volume Cracker (BHVC) through design iterations with a biomechanics scientist. We evaluated our asymmetric BHVC technique against standard 2D and widely used 3D interaction techniques with experts analyzing scanned beetle datasets. We found that our BHVC design significantly outperformed the other two techniques. This study contributes a practical 3DI design for scientists, documents lessons learned while redesigning for bare-hand trackers, and provides evidence suggesting that 3D interaction could improve volume data analysis for a variety of visual analysis tasks. Our contribution is in the realm of 3D user interfaces tightly integrated with visualization, for improving the effectiveness of visual analysis of volume datasets. Based on our experience, we also provide some insights into hardware-agnostic principles for design of effective interaction techniques.
Highlights
Across a broad range of scientific domains such as medical biology, geophysics, and astronomy, scientists use 3D techniques to scan humans, animals, man-made structures, the earth, or outer space
We employed the non-parametric ordinal logistic regression based on a Chisquare statistic for the ordinal variables, and a one-way analysis of variance (ANOVA) for the time metric
The experts’ preference of our bare-hand VC (BHVC) technique was close to significantly better over the standard 2D technique (AAS), whereas there was no significant difference between the interaction techniques in the perceived usefulness and ease of use
Summary
Across a broad range of scientific domains such as medical biology, geophysics, and astronomy, scientists use 3D techniques to scan humans, animals, man-made structures, the earth, or outer space. Raw volume data needs to be segmented, to separate the useful set of voxels from the occluding ones, before an effective visual analysis can be performed. We believe an interactive human intervention would be very efficient in this process to identify the useful set of voxels constituting the regions of interest in a raw volume and inform a semi-automatic segmentation of the entire volume. Questionnaire Metrics We ran pairwise correlation tests (Spearman’s ρ) between the participants’ weighted overall grade, their total time of task performance, and their self-reported ratings of fatigue, expertise with computers, frequency of computer use (for work and for fun), experience with volume data analysis (in general and with biomechanics), experience with the technique they used, experience with video games or 3D movies at the theater or at home, experience with Nintendo Wiimote, Sony Move, or Microsoft Kinect, and experience with 3D interaction for volume data analysis. We did not have a mandatory fatigue reporting metric, half of the AAS participants reported fatigue in their arms
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