The Foreground Bias: Initial Scene Representations Across the Depth Plane.

When you walk into a large room, you perceive visual information that is both close to you in depth and farther in the background. Here, we investigated how initial scene representations are affected by information across depth. We examined the role of background and foreground information on scene gist by using chimera scenes (images with a foreground and background from different scene categories). Across three experiments, we found a foreground bias: Information in the foreground initially had a strong influence on the interpretation of the scene. This bias persisted when the initial fixation position was on the scene background and when the task was changed to emphasize scene information. We concluded that the foreground bias arises from initial processing of scenes for understanding and suggests that scene information closer to the observer is initially prioritized. We discuss the implications for theories of scene and depth perception.

Examining the hierarchical nature of scene representations in memory.

How are scene representations stored in memory? Researchers have often posited that scene representations have a hierarchical structure with background elements providing a scaffold for more detailed foreground elements. To further investigate scene representation and the role of background and foreground information, we introduced a new stimulus set: chimera scenes, which have the central block of objects belonging to one scene category (foreground), and the surrounding structure belonging to another (background). We used a contextual cueing paradigm and emphasized the relative importance of each by having the target placed on either the background or foreground. In a transfer block, we found that though changes to the background were highly detrimental to search performance for background targets, search performance was only slightly affected by changes to either the foreground or the background for foreground targets. These results indicate that rather than a fixed hierarchy, the structure of scene representations are more aptly captured by a parallel model that stores information flexibly. (PsycINFO Database Record (c) 2019 APA, all rights reserved).