Abstract
Optic flow, the pattern of light generated in the visual field by motion of objects and the observer's body, serves as information that underwrites perception of events, actions, and affordances. This visual pattern informs the observer about their own actions in relation to their surroundings, as well as those of others. This study explored the limits of action detection for others as well as the role of optic flow. First-person videos were created using camera recordings of the actor's perspective as they performed various movements (jumping jacks, jumping, squatting, sitting, etc.). In three experiments participants attempted to detect the action from first-person video footage using open ended responses (Experiment 1), forced-choice responses (Experiment 2), and a match-to-sample paradigm (Experiment 3). It was discovered that some actions are more difficult to detect than others. When the task was challenging (Experiment 1) athletes were more accurate, but this was not the case in Experiments 2 and 3. All actions were identified above chance level across viewpoints, suggesting that invariant information was detected and used to perform the task.