Abstract

The big idea in computer graphics, what makes CG different from other ways of making images, is that CG represents images symbolically. The artist or designer creates a symbolic representation of the image, and the computer converts that representation to physical media. Because computational processes are so flexible, we have the freedom to invent any abstract representation that suits our needs. Somewhat surprisingly, most of computer graphics research has focused on the science and technology needed to make photorealistic images representing the physical world. In this talk, I will argue that we should shift our focus to developing techniques for manipulating abstract image representations. Historically, abstract imagery is more recent and more innovative than realistic imagery. Functionally, abstract image representations are often more informative and more expressive than realistic ones. More fundamentally, abstract image models better depict our mental models of the world, and are hence more useful to most people that use computer graphics in their work. In addition to motivating this line of research, I will outline some potentially promising research directions.

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