People use both their hands together cooperatively in many everyday activities. The modern computer interface fails to take advantage of this basic human ability, with the exception of the keyboard. However, the keyboard is limited in that it does not afford continuous spatial input. The computer mouse is perfectly suited for the point and click tasks that are the major method of manipulation within graphical user interfaces, but standard computers have a single mouse. A single mouse does not afford spatial coordination between the two hands within the graphical user interface. Although the advent of the Universal Serial Bus has made it possible to easily plug in many peripheral devices, including a second mouse, modern operating systems work on the assumption of a single spatial input stream. Thus, if a second mouse is plugged into a Macintosh computer, a Windows computer or a UNIX computer, the two mice control the same cursor. <br /><br /> Previous work in two-handed or bimanual interaction techniques has often followed the asymmetric interaction guidelines set out by Yves Guiard's Kinematic Chain Model. In asymmetric interaction, the hands are assigned different tasks, based on hand dominance. I show that there is an interesting class of desktop user interface tasks which can be classified as symmetric. A symmetric task is one in which the two hands contribute equally to the completion of a unified task. I show that dual-mouse symmetric interaction techniques outperform traditional single-mouse techniques as well as dual-mouse asymmetric techniques for these symmetric tasks. I also show that users prefer the symmetric interaction techniques for these naturally symmetric tasks.

People use both their hands together cooperatively in many everyday activities. The modern computer interface fails to take advantage of this basic human ability, with the exception of the keyboard. However, the keyboard is limited in that it does not afford continuous spatial input. The computer mouse is perfectly suited for the point and click tasks that are the major method of manipulation within graphical user interfaces, but standard computers have a single mouse. A single mouse does not afford spatial coordination between the two hands within the graphical user interface. Although the advent of the Universal Serial Bus has made it possible to easily plug in many peripheral devices, including a second mouse, modern operating systems work on the assumption of a single spatial input stream. Thus, if a second mouse is plugged into a Macintosh computer, a Windows computer or a UNIX computer, the two mice control the same cursor. <br /><br /> Previous work in two-handed or bimanual interaction techniques has often followed the asymmetric interaction guidelines set out by Yves Guiard's Kinematic Chain Model. In asymmetric interaction, the hands are assigned different tasks, based on hand dominance. I show that there is an interesting class of desktop user interface tasks which can be classified as symmetric. A symmetric task is one in which the two hands contribute equally to the completion of a unified task. I show that dual-mouse symmetric interaction techniques outperform traditional single-mouse techniques as well as dual-mouse asymmetric techniques for these symmetric tasks. I also show that users prefer the symmetric interaction techniques for these naturally symmetric tasks.

This dissertation provides empirical evidence for the effects of the fidelity of VR system components, and novel 3D interaction techniques for analyzing volume datasets. It provides domain-independent results based on an abstract task taxonomy for visual analysis of scientific datasets. Scientific data generated through various modalities e.g. computed tomography (CT), magnetic resonance imaging (MRI), etc. are in 3D spatial or volumetric format. Scientists from various domains e.g., geophysics, medical biology, etc. use visualizations to analyze data. This dissertation seeks to improve effectiveness of scientific visualizations. Traditional volume data analysis is performed on desktop computers with mouse and keyboard interfaces. Previous research and anecdotal experiences indicate improvements in volume data analysis in systems with very high fidelity of display and interaction (e.g., CAVE) over desktop environments. However, prior results are not generalizable beyond specific hardware platforms, or specific scientific domains and do not look into the effectiveness of 3D interaction techniques. We ran three controlled experiments to study the effects of a few components of VR system fidelity (field of regard, stereo and head tracking) on volume data analysis. We used volume data from paleontology, medical biology and biomechanics. Our results indicate that different components of system fidelity have different effects on the analysis of volume visualizations. One of our experiments provides evidence for validating the concept of Mixed Reality (MR) simulation. Our approach of controlled experimentation with MR simulation provides a methodology to generalize the effects of immersive virtual reality (VR) beyond individual systems. To generalize our (and other researchers') findings across disparate domains, we developed and evaluated a taxonomy of visual analysis tasks with volume visualizations. We report our empirical results tied to this taxonomy. We developed the Volume Cracker (VC) technique for improving the effectiveness of volume visualizations. This is a free-hand gesture-based novel 3D interaction (3DI) technique. We describe the design decisions in the development of the Volume Cracker (with a list of usability criteria), and provide the results from an evaluation study. Based on the results, we further demonstrate the design of a bare-hand version of the VC with the Leap Motion controller device. Our evaluations of the VC show the benefits of using 3DI over standard 2DI techniques. This body of work provides the building blocks for a three-way many-many-many mapping between the sets of VR system fidelity components, interaction techniques and visual analysis tasks with volume visualizations. Such a comprehensive mapping can inform the design of next-generation VR systems to improve the effectiveness of scientific data analysis. / Ph. D.