We evaluate the performance and usability of mouse-based, touch-based, and tangible interaction for manipulating objects in a 3D virtual environment. This comparison is a step toward a better understanding of the limitations and benefits of these existing interaction techniques, with the ultimate goal of facilitating the integration of different 3D data exploration environments into a single interaction continuum. For this purpose we analyze participants' performance in 3D manipulation using a docking task. We measured completion times, docking precision, as well as subjective criteria such as fatigue, workload, and preference. Our results show that the three input modalities provide similar levels of precision but require different interaction times. We also discuss our qualitative observations as well as people's preferences and put our findings into context of the practical application domain of 3D data analysis environments.
This paper describes and evaluates the design of four virtual controllers for use in rotating three-dimensional objects using the mouse. Three of four of these controllers are "new" in that they extend traditional direct manipulation techniques to a 3-D environment. User performance is compared during simple and complex rotation tasks. The results indicate faster performance for complex rotations using the new continuous axes controllers compared to more traditional slider approaches. No significant differences in accuracy for complex rotations were found across the virtual controllers.A second study compared the best of these four virtual controllers (the Virtual Sphere) to a control device by Evans, Tanner and Wein. No significant differences either in time to complete rotation task or accuracy of performance were found. All but one subject indicated they preferred the Virtual Sphere because it seemed more "natural". We report results from a formal user study of interactive 3D rotation using the mouse-driven Virtual Sphere and Arcball techniques, as well as multidimensional input techniques based on magnetic orientation sensors. MultidimensionaI input is often assumed to allow users to work quickly, but at the cost of precision, due to the instability of the hand moving in the open air. We show that, at least for the orientation matching task used in this experiment, users can take advantage of the integrated degrees of freedom provided by multidimensional input without necessarily sacrificing precision: using multidimensional input, users completed the experimental task up to 36 faster without any statistically detectable loss of accuracy. We also report detailed observations of common usability problems when first encountering the techniques. Our observations suggest some design issues for 3D input devices. For example, the physical form-factors of the 3D input device significantly influenced user acceptance of otherwise identical input sensors. The device should afford some tactile cues, so the user can feel its orientation without looking at it. In the absence of such cues, some test users were unsure of how to use the device. We present an experimental comparison of multi-touch and tangible user interfaces for basic interface actions. Twelve participants completed manipulation and acquisition tasks on an interactive surface in each of three conditions: tangible user interface; multi-touch; and mouse and puck. We found that interface control objects in the tangible condition were easiest to acquire and, once acquired, were easier more accurate to manipulate. Further qualitative analysis suggested that in the evaluated tasks tangibles offer greater adaptability of control and specifically highlighted a problem of exit error that can undermine fine-grained control in multi-touch interactions. We discuss the implications of these findings for interface design. We present the design and evaluation of FI3D, a direct-touch data exploration technique for 3D visualization spaces. The exploration of three-dimensional data is core to many tasks and domains involving scientific visualizations. Thus, effective data navigation techniques are essential to enable comprehension, understanding, and analysis of the information space. While evidence exists that touch can provide higher-bandwidth input, somesthetic information that is valuable when interacting with virtual worlds, and awareness when working in collaboration, scientific data exploration in 3D poses unique challenges to the development of effective data manipulations. We present a technique that provides touch interaction with 3D scientific data spaces in 7 DOF. This interaction does not require the presence of dedicated objects to constrain the mapping, a design decision important for many scientific datasets such as particle simulations in astronomy or physics. We report on an evaluation that compares the technique to conventional mouse-based interaction. Our results show that touch interaction is competitive in interaction speed for translation and integrated interaction, is easy to learn and use, and is preferred for exploration and wayfinding tasks. To further explore the applicability of our basic technique for other types of scientific visualizations we present a second case study, adjusting the interaction to the illustrative visualization of fiber tracts of the brain and the manipulation of cutting planes in this context.