UB - University at Buffalo, The State University of New York

Computer Vision and Information Visualization

Computer vision is an interdisciplinary field drawing on concepts from signal processing, artificial intelligence, neurophysiology, and perceptual psychology. The primary goal of computer vision research is to endow artificial systems with the capacity to see and understand visual imagery at a level rivaling or exceeding human vision. One part of research at UB focuses on computational theories for contour image analysis of things such as technical drawings, architectural plans, maps, and even cartoons to enable such images to be used in human and computer interaction. With psychophysical experiments, aspects of contour images of perceptual significance to humans are identified.

Active foveal vision explores the use of cameras whose resolution decreases from center to periphery of the field of view, similar to the human retina. This research focuses on the design of computer chips to implement a system that registers a central region of interest with high detail while displaying a larger zone at lower resolution, and on the algorithms that permit variable resolution image sequences to be understood.

Our fundamental research includes developing techniques for visualizing common data-structures such as graphs and multidimensional data sets, and visualizing molecular structures. Our applied research includes visualizing data from practical applications, such as bioinformatics, software engineering, pharmacokinetics, engineering and design, bioimaging, and digital art.

Faculty

• Peter Scott (Associate Professor)
• Jason Corso (Assistant Professor)
• Robert Platt (Assistant Professor)

Knowledge Media Lab Projects

• Using Technology to Improve Learning and Decrease Cost
  
• Community Linked Interdisciplinary Research

Researchers include Carl Alphonce and Helene Kershner.