ITR: Collaborative Research: Generating an Accurate Sense of Depth and Size Using Computer Graphics

University Of Utah, Salt Lake City UT

Investigators

Abstract

Despite impressive gains in realism over the last decade, computer graphics is currently unable to effectively generate images of objects and environments that look large. This is mostly because computer graphics is poor at conveying information about absolute depth. The goal of this project is to demonstrate that it is possible to significantly improve the sense of depth and scale in computer graphics if rendering methods are developed with specific attention to the need to convey cues for absolute depth. Accomplishing this goal will require new insights into the 3D information extractable from 2D images, modifications to graphics algorithms in order to better render salient information, and sophisticated perceptual experimentation to validate that people can actually see the intended 3D space. The PI's approach will be to draw upon the results and methods of computational vision in ways that have not previously been done in the computer graphics community. Computational vision provides insights into the intrinsic constraints on how information about 3D space can be recovered from 2D images. In particular, the computational analysis of vision points out the important distinction between relative depth judgments and absolute depth judgments. Surprisingly few of the commonly studied image cues are in fact sufficient to provide information about absolute depth. Of those that do, several cannot be exploited in computer graphics due to fundamental limitations in display technology and our inability to precisely control viewing conditions except in immersive environments. The research will impact a broad range of graphics applications in which accurate spatial information needs to be conveyed, including education and training, design and prototyping, and telepresence.