Perceptual and computational analysis of critical features for biological motion.

Among the most common events in our daily lives is seeing people in action. Scientists have accumulated evidence suggesting humans may have developed specialized mechanisms for recognizing these visual events. In the current experiments, we apply the "bubbles" technique to construct space-time classification movies that reveal the key features human observers use to discriminate biological motion stimuli (point-light and stick figure walkers). We find that observers rely on similar features for both types of stimuli, namely, form information in the upper body and dynamic information in the relative motion of the limbs. To measure the contributions of motion and form analyses in this task, we computed classification movies from the responses of a biologically plausible model that can discriminate biological motion patterns (M. A. Giese & T. Poggio, 2003). The model classification movies reveal similar key features to observers, with the model's motion and form pathways each capturing unique aspects of human performance. In a second experiment, we computed classification movies derived from trials of varying exposure times (67-267 ms) and demonstrate the transition to form-based strategies as motion information becomes less available. Overall, these results highlight the relative contributions of motion and form computations to biological motion perception.