Recognizing Scenes Containing Consistent or Inconsistent Objects


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.

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