Gold Jason M, Barker Jarrett D, Barr Shawn, Bittner Jennifer L, Bromfield W Drew, Chu Nicole, Goode Roy A, Lee Doori, Simmons Michael, Srinath Aparna
Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA.
J Vis. 2013 Apr 25;13(5):23. doi: 10.1167/13.5.23.
Unlike frozen snapshots of facial expressions that we often see in photographs, natural facial expressions are dynamic events that unfold in a particular fashion over time. But how important are the temporal properties of expressions for our ability to reliably extract information about a person's emotional state? We addressed this question experimentally by gauging human performance in recognizing facial expressions with varying temporal properties relative to that of a statistically optimal ("ideal") observer. We found that people recognized emotions just as efficiently when viewing them as naturally evolving dynamic events, temporally reversed events, temporally randomized events, or single images frozen in time. Our results suggest that the dynamic properties of human facial movements may play a surprisingly small role in people's ability to infer the emotional states of others from their facial expressions.
与我们在照片中经常看到的面部表情的定格画面不同，自然的面部表情是随着时间以特定方式展开的动态事件。但是表情的时间特性对于我们可靠地提取有关一个人的情绪状态信息的能力有多重要呢？我们通过衡量人类在识别具有相对于统计上最优（“理想”）观察者不同时间特性的面部表情时的表现，通过实验解决了这个问题。我们发现，人们在将情绪视为自然演变的动态事件、时间反转的事件、时间随机化的事件或时间定格的单张图像来观看时，识别情绪的效率是一样的。我们的结果表明，人类面部运动的动态特性在人们从面部表情推断他人情绪状态的能力中可能起着惊人的小作用。
