Understanding biological motion

心理科学中的一个主要问题是，人们如何推断他人的意图。人类非常擅长预测其他人的行为，并对他们的意图和目标做出推断。目前的研究考察了人类是如何从他人的身体运动中做出这样的推断的。这项工作是由生物运动理解的计算理论指导的，该理论将动作表示量化，使人们能够在动作识别和预测中做出推断。更大的目标是解释感知和推理如何协同工作，以推断隐藏的目标和意图。这项拟议的研究在几个领域具有广泛的影响。大多数人的推理能力超过了当今最好的机器视觉系统。例如，在波士顿马拉松爆炸案的调查中，可以从监控摄像系统获得大量视频，但导致逮捕的是训练有素的人眼。人类调查人员逐帧仔细检查了数百个小时的视频，找出了表现出可疑行为模式的嫌疑人。因此，了解人类是如何对行为做出推断和预测的，将在指导开发更先进的机器视觉系统方面发挥重要作用，这些系统在法医科学和许多其他现实世界的应用中都是有用的。此外，患有自闭症或非语言学习障碍的人通常难以推断观察到的行为的含义。对行动理解背后的关键计算成分的调查可能会潜在地指导行为干预的发展，以促进理解行动的补偿策略。

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.