Abstract
We can quickly and effortlessly evaluate whether a tower of blocks will collapse or a stack of dishes will come crashing down. What is the nature of this ability? Although such "intuitive physics" are traditionally associated with higher-level reasoning, here we explore the possibility that such sophisticated physical intuitions are underwritten by more basic processes -- and specifically whether visual attention and memory are automatically drawn toward physically relevant features. In a modified change-detection task, an image of a physically stable block-tower was briefly displayed, after which it disappeared and was replaced either in the same configuration or with one block slightly displaced. On some trials, this change upset the tower's balance, rendering it unstable; on other trials, the change was identical in magnitude but did not alter the tower's stability. Detection was reliably better for changes to blocks that altered overall stability, compared to either (1) equivalent changes to the same blocks that did not influence stability, or (2) equivalent changes to different blocks. Critically, this pattern was robust even though stability was entirely incidental to the task. Follow-up studies demonstrated that improved change detection based on physical stability was reliable even when attending to physical stability could confer no strategic advantage, and was robust even for observers who never consciously noticed any variation in the towers' (in)stability. Further work isolated perceived stability, per se: when the towers' ground-truth stability (according to physics) was contrasted with subjectively perceived stability (as rated by independent subjects), change-detection was better predicted by how stable the towers *looked* than by how stable they actually were. Collectively, this work shows how basic processes of attention and memory are sensitive to a scene's underlying physics, and how selective attention is automatically drawn to those objects and features that are especially physically relevant.
Meeting abstract presented at VSS 2016