How long to get to the “gist” of real-world natural scenes?

TLDR

The study examined how quickly humans can extract the gist of natural scenes in rapid categorization tasks. Experiment 1 had participants perform go/no‑go categorization of colour images of real‑world (Sea, Mountain) and artificial (Indoor, Urban) scenes, while Experiment 2 compared colour and grey‑level versions of the same scenes, with all pictures flashed for 26 ms. Both experiments showed that the gist of real‑world scenes can be extracted with >90 % accuracy within 400–460 ms, with early responses as short as 260–300 ms; natural scenes were processed faster than artificial ones, colour‑diagnostic categories benefited from colour cues, and scene‑categorization speed was compared to object categorization.

Abstract

This study aimed at assessing the processing time of a natural scene in a fast categorization task of its context or "gist". In Experiment 1, human subjects performed 4 go/no-go categorization tasks in succession with colour pictures of real-world scenes belonging to 2 natural categories: "Sea" and "mountain", and 2 artificial categories: "Indoor" and "urban". Experiment 2 used colour and grey-level scenes in the same tasks to assess the role of colour cues on performance. Pictures were flashed for 26 ms. Both experiments showed that the gist of real-world scenes can be extracted with high accuracy (>90%), short median RT (400-460 ms) and early responses triggered with latencies as short as 260-300 ms. Natural scenes were processed faster than artificial scenes. Categories for which colour could have a diagnostic value were processed faster in colour than in grey. Finally, processing speed is compared for scene and object categorization tasks.