Cornell is a leader in computer graphics, a broad interdisciplinary field encompassing a growing range of applications from science to communication to entertainment. Research in computer graphics draws on many specialties; among other fields it involves algorithms, physics, psychology, computation, computer vision, and architecture.

The Program of Computer Graphics (PCG), an interdisciplinary research center with close ties to the Computer Science Department, was one of the first laboratories to do research in graphics. Established in 1974, the PCG has made breakthrough contributions in areas including light reflection models, physics-based accurate rendering, and visual perception for graphics. Current research areas include realistic materials; scalable high-quality rendering; animation; physical simulation for graphics, haptics, and sound rendering; and vision and perception.

Over the years, the PCG has brought together students from different disciplines: computer science; physics; mathematics; electrical, structural, and mechanical engineering; architecture; and psychology. The state-of-the-art facility includes a 128-processor computing cluster, a sophisticated light measurement laboratory, a high-resolution tiled projection display, a 3D scanner, haptic interfaces, and many other tools for advanced research.

Faculty: Research Descriptions

Kavita Bala works on computer graphics algorithms for rendering and modeling complex virtual worlds. A fundamental challenge is efficiently capturing the visual complexity and richness of real scenes. By understanding and exploiting the limits of the human visual system, new rendering and modeling algorithms become possible that scale to real-world complexity. Bala's research interests include scalable graphics for interactive rendering; perceptually-based rendering; image-based modeling and texturing; cinematic relighting; and feature-based rendering and texturing. Applications range from cultural heritage and preservation, engineering design, games and movies, virtual-reality training, architectural planning, and e-commerce.

Donald Greenberg, the founder of the Program of Computer Graphics, has been researching and teaching in the field of computer graphics from 1966. During the last 15 years, he has been primarily concerned with research advancing the state-of-the-art in computer graphics and with utilizing these techniques as they may be applied to a variety of disciplines. His specialities include hidden surface algorithms, geometric modeling, color science, and realistic image generation. Donald Greenberg is the Jacob Gould Schurman Professor of Computer Graphics and the Director of the Program of Computer Graphics.

Doug James has his primary teaching and research interests in computer graphics, physically based animation, computational geometry, scientific computing, dimensional model reduction, computational robotics, and haptic force-feedback rendering. Some typical application areas are computer animation, virtual prototyping and assembly planning, and interactive soft-tissue simulation for virtual medicine. His work emphasizes algorithms that can exploit the structure and information content of physical phenomena to permit faster and better simulations. An important research theme has been the design of amortized algorithms that leverage preprocessing to accelerate physical simulations. He is currently exploring algorithms to accelerate processing of discrete deformable systems: fast integration of solid dynamics, output-sensitive collision detection techniques, fast contact resolution, force-feedback haptic rendering, real-time acoustic radiation, and appearance modeling. He is also researching ways to reuse physical motion databases to enable interactive display and to provide animators with more control over physical simulation content.

Steve Marschner works on material models and model capture, often using techniques that draw from computer vision. Material modeling is the fundamental problem of understanding and simulating the interaction of light with materials. Existing models describe simple materials well, but we need new insights before we can accommodate the complex mixtures of materials that occur commonly in reality. Model capture focuses on developing methods for building richly detailed models using measurements from real objects. This work is part of a major trend that is increasingly blurring the distinction between vision and graphics: more and more graphics applications have extended the limits of traditional modeling by using a mixture of vision and graphics techniques to import complexity from the real world.

Program of Computer Graphics

Researchers

Kavita Bala
Don Greenberg
Doug James
Steve Marschner
Ken Torrance
Bruce Walter

Related Areas

Scientific and Parallel Computing
Artificial Intelligence

Related researchers

Paul Chew
Jim Ferwerda
Dan Huttenlocher
Ramin Zabih