The Processing Speed of Scene Categorization at Multiple Levels of Description: The Superordinate Advantage Revisited

Abstract

Recent studies have sought to determine which levels of categories are processed first in visual scene categorization and have shown that the natural and man-made superordinate-level categories are understood faster than are basic-level categories. The current study examined the robustness of the superordinate-level advantage in a visual scene categorization task. A go/no-go categorization task was evaluated with response time distribution analysis using an ex-Gaussian template. A visual scene was categorized as either superordinate or basic level, and two basic-level categories forming a superordinate category were judged as either similar or dissimilar to each other. First, outdoor/ indoor groups and natural/man-made were used as superordinate categories to investigate whether the advantage could be generalized beyond the natural/man-made boundary. Second, a set of images forming a superordinate category was manipulated. We predicted that decreasing image set similarity within the superordinate-level category would work against the speed advantage. We found that basic-level categorization was faster than outdoor/indoor categorization when the outdoor category comprised dissimilar basic-level categories. Our results indicate that the superordinate-level advantage in visual scene categorization is labile across different categories and category structures.