Understanding biological motion

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

A major issue in the psychological sciences is how people can infer the intentions of others. Humans are remarkably adept at predicting the actions of other people and making inferences about their intention and goals. The present investigation examines how humans make such inferences from the physical movements of others. The work is guided by a computational theory of biological motion understanding that quantifies the action representations that allow people to make inferences in action recognition and prediction. The larger goal is to explain how perception and reasoning operate synergistically to infer hidden goals and intentions. The proposed research has broad impact in several domains. The inference capacity of most people exceeds that of today's best machine vision systems. For example, in the investigation of the bombing at the Boston marathon, extensive video from surveillance camera systems was available but it was the trained human eye that led to arrests. Human investigators scrutinized hundreds of hours of videos frame by frame and identified suspects who displayed suspicious behavioral patterns. Hence, understanding how humans make inferences and predictions about actions will play an important role in guiding the development of more advanced machine vision systems, useful in forensic sciences as well as many other real-world applications. In addition, individuals with autism or nonverbal learning disabilities often show difficulty in inferring the meaning of observed actions. Investigation of the key computational components underlying action understanding may potentially guide the development of behavioral interventions to facilitate compensatory strategies for understanding actions.