Abstract
Picture memory consistently indicate that viewers extend their mental representations to include areas of the scene that were not visible in the partial view presented in the picture. This "boundary extension" can provide useful predictions regarding the layout of areas of the scene that are not visually available at a given moment. The current study tested whether people extend the boundaries of areas seen through scene-intrinsic apertures such as doors, pathways, and windows. Participants viewed sixteen scenes that included such an apertures, with another scene visible through it. For example, a picture showed a hallway ("external scene" ) with the front door open showing the front yard ("internal scene"). These pictures were intermixed with other pictures of scenes showing no such combinations. To ensure that viewers played attention to the "internal scene", participants were asked to indicate whether the scene was an indoor, outdoor, or a combination scene (like the example above). After the presentation, viewers were asked to select the version of the picture they remember from four possible versions. Given the robustness of Boundary Extension, the exact target picture was not available. Rather, the four choices included the following: an overall extended version (a typical extended version with no extension of the "internal scene"), a version where only the "internal scene" was extended, a version where only the "external scene" was extended (resulting in a restriction of the "internal scene") and a version where both the internal and the external scenes were extended differentially. Results indicated Boundary Extension of views seen through the aperture as participants selected the versions with the extended "internal scenes" more often than the versions where only the picture boundaries were extended. This extension for naturally occurring boundaries rather than just arbitrarily imposed picture boundaries speaks to the everyday use of such layout extrapolations.
Meeting abstract presented at VSS 2017