This is the first year funding of a five-year continuing award. This research program is geared towards making significant advances to the science and engineering of visual information processing, and addresses fundamental problems in the fields of computational vision, computer graphics, and human-machine interactions. Today, images and video clips are ubiquitous on the internet, digital video is changing the way entertainment is produced, distance learning is used in various facets of education, and advanced visual interfaces to machines are around the corner. However, at present there are severe limits to the extent to which a user can benefit from visual information, because virtually all of this information is presented in its raw form, that is, the way it was captured. The goal of this project is to develop the technical tools needed to achieve a variety of complex manipulations of visual data. These tools will enable a user to freely explore, interact with, and create variations of the physical world being presented. For instance, a user may remove and add objects to an image of a scene, vary lighting conditions, change the materials of surfaces, or view the scene from a novel perspective.

This project encompasses a comprehensive research program for creating the science and technology base required to enable such advanced manipulations of visual data. The general research problem may be stated as follows: Capturing, understanding, and predicting the appearance of our everyday world. Success in this domain of research necessitates a unified approach to open problems in two fields: computational vision and computer graphics. The research effort will focus on five pertinent areas: sensing, modeling, estimation, generation, and evaluation. The tangible contributions will be in the form of sensors that provide new types of visual information; complex models of materials, reflectances and textures; estimation algorithms that use the team's new models to recover scene properties from minimal data; advanced rendering techniques; and a set of comprehensive image/video databases for evaluation of work in this field. The results will impact numerous application domains, including digital imaging, entertainment, virtual environments, distance learning, e-commerce, interactive product design, art restoration, architectural modeling, restorative surgery, and surface inspection.

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
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Daniel F. DeMenthon
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Columbia University
New York
United States
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