Abstract
Visual processing recovers not only seemingly low-level features such as color and orientation, but also seemingly higher-level properties such as animacy and intentionality. Even abstract geometric shapes are automatically seen as alive and goal-directed if they move in certain ways. What cues trigger perceived animacy? Researchers have traditionally focused on the local motions of objects, but what may really matter is how objects move with respect to the surrounding scene. Here we demonstrate how movements that signal animacy in one context may be perceived radically differently in the context of another scene. Observers viewed animations containing a stationary central disc and a peripheral disc, which moved around it haphazardly. A background texture (a map of Tokyo) moved behind the discs. For half of observers, the background moved generally along the vector from the peripheral disc to the central disc (as if the discs were moving together over the background, with the central disc always behind the peripheral disc); for the other half of observers, the background moved generally along the vector from the central disc to the peripheral disc. Observers in the first condition overwhelming perceived the central disc as chasing the peripheral disc, while observers in the second condition experienced the reverse. A second study explored objective detection: observers discriminated displays in which a central 'wolf' disc chased a peripheral 'sheep' disc from inanimate control displays in which the wolf instead chased the sheep's (invisible) mirror image. Although chasing was always signaled by the wolf and sheep's close proximity, detection was accurate when the background moved along the vector from the sheep to the wolf, but was poor when the background moved in an uncorrelated manner (controlling for low-level motion). These dramatic context effects indicate that spatiotemporal patterns signaling animacy are detected with reference to a scene-centered coordinate system.
Meeting abstract presented at VSS 2017