Visual Computing: At the Crossroads of Realism, Modeling, and Perception

One of the important applications of such a coupled cluster is a better understanding and fast solutions to protein modeling through a visualization-assisted computational steering environment. I will give an overview of our system to efficiently solve the non-linear Poisson-Boltzmann equation governing molecular electrostatics. We use pre-computed accumulation of transparency with spherical-harmonics-based compression to accelerate volume rendering of molecular electrostatics.

Spherical-harmonics-based functions are also being used to efficiently compute illumination for 3D graphics scenes. I will present our approach to representing the six-dimensional integrals of bidirectional surface scattering reflectance distribution functions (BSSRDFs) to render scattering effects in translucent materials interactively. We discuss how we approximate the scattered reflectance field by a 4D representation through pre-processing the neighborhood scattering radiance transfer integrals.

Recent research in perception of illumination suggests that the discrepancies in illumination are not processed at the pre-attentive stage of the human visual system processing. In fact, artists have been using inconsistent lighting for centuries. We have explored the implications of globally discrepant lighting for enhancing the visualization of scientific datasets. I will overview our system Light Collages which is a lighting design system for effective visualization that automatically places lights to convey a better perception of shape with globally discrepant lighting.

As the data models get larger, graphics hardware improves, displays achieve higher resolution, and sophisticated methods of lighting design and illumination enable better depiction of detail, human comprehension becomes the ultimate bottleneck. We have developed a human-perception inspired computational model of visual saliency for 3D graphics meshes based on a center-surround mechanism. I shall give an overview of our mesh saliency approach and discuss its applications.

Speaker Bio: Amitabh Varshney is an Associate Professor of Computer Science at the University of Maryland. His research has addressed challenges in 3D interactive graphics and visualization for large graphics datasets by reconciling realism with interactivity through multiresolution techniques and high-performance computing. He has served as the Papers Chair for IEEE Visualization 2000 and 2001, Program Chair for IEEE Visualization 2005, and is the Conference Chair for IEEE Visualization 2006. In addition, he has served on several program and conference committees and journal editorial boards. Varshney received the NSF CAREER award in 1995 and the first IEEE Visualization Technical Achievement Award in 2004. Varshney received a B.Tech. in Computer Science from the Indian Institute of Technology Delhi in 1989 and an MS and PhD in Computer Science from the University of North Carolina at Chapel Hill in 1991 and 1994.

Presentation Slides: PDF

Note: Visitors from outside NIST must contact Robin Bickel; (301) 975-3668; at least 24 hours in advance.