Recognizing Scenes Containing Consistent or Inconsistent Objects

Abstract

How does object perception influence scene perception? A recent study of ultrarapid scene categorization (Joubert et al., 2007) reported facilitated scene categorization for scenes with consistent objects compared to scenes with inconsistent objects. One proposal for this consistent-object advantage is that ultrarapid scene categorization is influenced directly by explicit recognition of particular objects in the scene. We instead asked whether a simpler mechanism that relied only on scene categorization without any explicit object recognition could explain the consistent-object advantage. We combined a computational model of scene recognition based on global scene statistics (Oliva & Torralba, 2001) with a diffusion model (Ratcliff, 1978) of perceptual decision making. Simulations show that this model is sufficient to account for the consistent-object advantage. Importantly, this effect need not arise from explicit object recognition, but from the inherent influence certain objects have on the global scene statistics diagnostic for scene categorization.


Back to Saturday Papers