Perception and categorization or real world scenes

描述（由申请人提供）：

DESCRIPTION (provided by applicant): The application addresses a fundamental tension in visual cognition: how are human observers able to recognize the semantics of a complex real world scene image at a glance? Since the seminal work of Mary Potter, a number of experimental studies have demonstrated that we identify a surprising amount of information from a single glance at a scene. We can recognize its semantic category (e.g. a street), some objects and regions (e.g. a red car on the left) and other characteristics of the space that the scene subtends in the real world (e.g. perspective). This information refers to the "gist" of the scene and can be identified as quickly and as accurately as a single object. The principal aim of this project is to define the perceptual content of the image information acquired during a glance at scene photographs. In this application, we consider the case of the image being conceptualized in short-term memory. We aim to propose an experimental paradigm that allows the comparison of the quantity of information common to pairs of scene images. The research program introduces an innovative image similarity measure that defines the exact quantity of spatial and spectral components common to images that share the same semantic category. The results of the proposed research program shall provide researchers in visual cognition with the knowledge about the quantity of image information that, on average, adult human observers are seeing and remembering within a brief exposure to a novel picture. The research should demonstrate that the quantity of information varies with the task the observer has to perform. More precisely, the study aims to explore the information that human observers may use when recognizing a scene at different levels of abstraction (its superordinate level, its basic-level and its subordinate level of description).