Abstract
Scientific visualization enables researchers to extract understanding from data through visual representations. Interactive visualizations are particularly powerful for exploration of data, but they require that representations can be built and manipulated in real time; this is especially difficult for large or complex data. Advances in human-computer interfaces also provide for new ways to engage with visualizations. This dissertation covers visualization systems that address challenges in visual representation, real-time rendering, and natural interaction. The first domain we consider in this dissertation is robotics. In particular, we focus on the topics of motion and autonomous behavior for robots. We cover three projects in robotics: (1) dynamically generated visualizations of robot behaviors in a multi-agent environment; (2) exploring 3D robot configuration spaces; (3) interactively mapping human motions to humanoid robots with visual feedback. The final project is in the medical domain. Surgeons rely on medical imaging for preoperative planning and diagnosis, but they also use it intraoperatively for guidance during a procedure. We developed a system with doctors at the Oregon Health and Science University Hospital for surgical navigation of MR and CT images using a touchless, gesture-based interface. Our medical visualization software provides enhanced understanding of complex anatomical relationships and introduces novel interactions with volumetric data.