mechanisms

Abstract not found

Subjects were asked to discriminate scenes after very brief exposures (37-69 ms). Their performance was always above chance and increased with exposure duration, confirming that subjects can get the gist of a scene with one fixation. We propose that a simple texture analysis of the image can provide a useful cue towards rapid scene identification. Our

Determining the visual fidelity of an image is a fundamental problem in computer graphics. When is an image good enough; i.e. when does it convey a convincing representation of a scene? Most graphics algorithms either aim to compute a physically accurate solution matching the real world, or they leave judgments of fidelity entirely up to the end user. The former is often computationally intractable, and the latter is ad-hoc since it cannot be generalized or predicted. In this dissertation, we chart a new course between these two approaches. We propose visual equivalence, a new standard of image fidelity that focuses on what is visually important to the observer: the appearance of the scene, consisting of impressions of shapes, materials, and lighting. Under visual equivalence, an image with noticeable, pixel-by-pixel differences from a perfect reference can still be a high fidelity representation of the same scene, provided it conveys the same impression of scene appearance. This appearance-preserving standard is, to our knowledge, the first approach to image fidelity that permits judgments of this kind. We present an end-to-end psychophysical and algorithmic investigation of visual equivalence,