Scientific visualization of a computer model of global carbon dioxide.

The Advanced Visualization Lab (AVL) is part of the the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. The AVL is led by Professor Donna Cox, who coined the term "Renaissance Team", with the belief that bringing together specialists of diverse backgrounds creates a team that is greater than the sum of its parts, and members of the AVL team reflect that in our interdisciplinarity. We specialize in creating high-quality cinematic scientific visualizations of supercomputer simulations for public outreach.

This visualization shows ocean surface currents around the world during the period from June 2005 through December 2007. The visualization does not include a narration or annotations; the goal was to use ocean flow data to create a simple, visceral experience.

More powerful computer hardware and software has enabled the development of numerous depth-cue techniques to depict the three-dimensional (3D) characteristics of computer-generated imagery. Particularly, the role of stereoscopic viewing in promoting the depth perception of objects in 3D space has been widely studied. However, there has been little study of the use of cast shadows in this context, and few investigations of how computer-generated depth cues are perceptually integrated. To investigate these issues, subjects: 1) position a sphere to complete a directional vector/vector segment extending in space and 2) resize a sphere to match the perceived size of a second sphere displaced in space. Task accuracies and response times are recorded under the following conditions: 1) stereoscopic, and monoscopic, scene viewing; 2) objects casting zero, or one shadow; 3) flat, and zig-zag, background surface shapes; and 4) solid and checkerboard background surface textures. The results suggest that, of the cues considered, stereo viewing has a consistently beneficial effect on positioning and resizing spheres in depth. However, objects casting shadows improve positioning accuracy to a level afforded by stereo viewing. Finally, more complex scene backgrounds impair positioning and resizing task performances. Implications for the design of effective 3D user interfaces are discussed.

This paper examines a series of NASA outreach visualizations created using several layers of remote sensing satellite data ranging from 4-kilometers per pixel to I-meter per pixel. The viewer is taken on a seamless, cloud free journey from a global view of the Earth down to ground level where buildings, streets, and cars are visible. The visualizations were produced using a procedural shader that takes advantage of accurate georegistration and color matching between images. The shader accurately and efficiently maps the data sets to geometry allowing for animations with few perceptual transitions among data sets. We developed a pipeline to facilitate the production of over twenty zoom visualizations. Millions of people have seen these visualizations through national and international media coverage.

More powerful contemporary computer hardware has enabled the development and exploration of a wide variety of techniques to depict spatial characteristics of computer-generated objects in three-dimensional (3D) space.Particularly, the role of stereoscopic viewing and the use of object motion to reflect the position and size of objects in 3D space have been extensively studied.However, the effective use of computer-rendered object shadows to provide spatial information about the relative position and size of objects in virtual space has not.Subjects perform two tasks with 3D geometric patterns of objects presented on a computer screen: (1) positioning the object to complete a symmetrical geometric figure and (2) resizing the object to match the size of other objects.Performance accuracy and speed are recorded under the following conditions: (1) objects casting shadows on and off, (2) shadows from one or two light sources (nested within the shadows-on condition), (3) stereoscopic and monoscopic viewing, and (4) different scene backgrounds: flat plane (i.e., floor), "stair-step" floor with no walls, and floor with walls (i.e., room).The use of object shadows as depth cues enhances the accuracy (but not the speed) of object positioning, but does not enhance either the accuracy or the speed of object resizing.Moreover, the object shadows are not as effective as stereoscopic viewing in facilitating both positioning-task and resizing-task performances.Furthermore, task performances degrade with the stair-step scene background and when the number of shadowing light sources increases from one to two.