From Blobs to Boundary Edges: Evidence for Time- and Spatial-Scale-Dependent Scene Recognition

Abstract

In very fast recognition tasks, scenes are identified as fast as isolated objects How can this efficiency be achieved, considering the large number of component objects and interfering factors, such as cast shadows and occlusions? Scene categories tend to have distinct and typical spatial organizations of their major components If human perceptual structures were tuned to extract this information early in processing, a coarse-to-fine process could account for efficient scene recognition A coarse description of the input scene (oriented “blobs” in a particular spatial organization) would initiate recognition before the identity of the objects is processed We report two experiments that contrast the respective roles of coarse and fine information in fast identification of natural scenes The first experiment investigated whether coarse and fine information were used at different stages of processing The second experiment tested whether coarse-to-fine processing accounts for fast scene categorization The data suggest that recognition occurs at both coarse and fine spatial scales By attending first to the coarse scale, the visual system can get a quick and rough estimate of the input to activate scene schemas in memory, attending to fine information allows refinement, or refutation, of the raw estimate