Abstract
Previous research has shown robust, systematic aesthetic preferences for the horizontal position and facing direction of single objects within rectangular frames (Palmer, Gardner & Wickens, 2008; Gardner & Palmer, VSS-2006, VSS-2008). People prefer an object to be laterally positioned near the center (the “center bias”) and to face into, rather than out of, the frame (the “inward bias”). Similar, but more complex, biases occur in the vertical dimension: a “lower bias” for objects supported from below and viewed from above (a bowl on a table), an “upper bias” for objects supported from above and viewed from below (a light fixture on a ceiling), and a “center bias” for symmetrical images of gravitationally unsupported objects (a flying eagle viewed from directly below or above). The object's characteristic ground-relative position in the world also affects people's preferences for vertical placement: eagles are preferred higher and stingrays lower in the frame. Real-world compatibility in the size domain also affects aesthetic judgments: a mouse picture is preferred when it is smaller within the frame and an elephant when it is larger (Konkle & Oliva VSS-2007). Canonical perspectives (Palmer, Rosch & Chase, 1981) also produce higher preference ratings for pictures of objects (Khalil & McBeath, VSS-2006). These effects can be unified by the “representational transparency” hypothesis: observers prefer images in which the spatial characteristics of depicted objects in the world are optimally reflected in analogous spatial properties of the image. This has both a real-world-position component (eagles higher, stingrays lower) and a viewer-relative component (objects viewed from below are preferred higher, objects viewed from above are preferred lower). Representational transparency provides a reasonable first-order approximation of default expectations for people's aesthetic responses, but greater aesthetic value often requires violating these expectations in meaningful ways that reflect the intentions of the artist.
NSF Grant BCS-0745820, Google.