Collaborative Proposal: Automated Measurements of Infant Facial Expressions and Human Ratings of Their Emotional Intensity

婴儿的微笑可以预测以后的适应功能，但很少有人知道的时间过程中的婴儿微笑或其感知的情绪强度。这个合作项目将基于计算机的婴儿微笑测量与父母对这些微笑的评级相结合。该项目的目标是了解婴儿如何微笑，并记录使婴儿微笑或多或少显得快乐的特征。为了了解婴儿如何微笑，将使用计算机软件（CMU/Pitt自动面部图像分析，v. IV）测量50名6个月大婴儿的微笑强度和同时出现的张口度。这些客观的测量将用于记录婴儿微笑如何形成，高峰，并及时溶解。也就是说，我们将创建微笑的实时肖像，以更全面地了解积极的情绪功能。我们将研究微笑强度和张口度之间的统计学关联，以及微笑和婴儿之间的差异，即微笑的这些组成部分之间的关联有多强。补充图形和统计方法将鼓励情绪功能的动态帐户和情绪在学习和发展中的作用的研究新途径。 该项目使用评级研究来记录使婴儿微笑看起来或多或少快乐的特征。婴儿和大学生的父母都将被要求对微笑的静态图像和视频剪辑的情绪强度进行评级。然后，自动测量微笑的强度和嘴巴张开度，以预测积极情绪强度的评级。积极的研究结果将验证自动测量的婴儿微笑的具体功能，婴儿快乐的情绪强度的指数。在这个项目中，领先的婴儿情感研究人员将与尖端的自动面部测量团队合作，调查婴儿的微笑。婴儿使用积极的面部表情来表达情感和与他人交流。在体内婴儿情绪表达的时间过程的基本知识承诺规范和妥协的情绪功能和发展的客观看法。为此，将向提出请求的调查人员提供所获得的数字化面部表情及其自动测量数据库。这些客观的描述将由父母和天真的观察者对这些表达的情感强度的感知来补充。这将验证自动化测量的情感意义，并有助于开发具有广泛影响力的自动编码工具。

Infant smiles can predict later adaptive functioning, but little is known about the temporal course of infant smiles or their perceived emotional intensity. This collaborative project combines computer-based measurements of infant smiles with parents' ratings of those smiles. The project goals are to understand how infants smile, and to document the features that make infant smiles appear more or less joyful. To understand how infants smile, the smile strength and co-occurring mouth opening of 50 six-month-old infants' smiles will be measured using computer software (CMU/Pitt Automated Facial Image Analysis, v. IV). These objective measurements will be used to document how infant smile form, peak, and dissolve in time. That is, we will create real-time portraits of smiles to more fully understand positive emotional functioning. Statistical associations between smile strength and mouth opening will be examined, as will differences - both between smiles and between infants - in how strongly these components of smiles are associated. Complementary graphical and statistical approaches will encourage dynamic accounts of emotional functioning and new avenues of research on the role of emotion in learning and development. The project uses rating studies to document features that make infant smiles appear more or less joyful. Both parents of infants and undergraduates will be asked to rate the emotional intensity of both still images and video clips of smiles. Automated measurements of smile strength and mouth opening will then be used to predict ratings of positive emotional intensity. Positive findings would validate automated measurements of specific features of infant smiles as indices of infant joyful emotional intensity. In this project, leading infant emotion researchers will collaborate with a cutting-edge automated facial measurement team to investigate infants' smiles. Infants use positive facial expressions to express emotions and communicate with others. Basic knowledge of the temporal course of in vivo infant emotional expressions promises an objective view of normative and compromised emotional functioning and development. To that end, the acquired database of digitized facial expressions and their automated measurements will be made available to requesting investigators. These objective descriptions will be complemented by parental and naive observers' perceptions of the emotional intensity of these expressions. This will validate the emotional significance of the automated measurements, and contribute to the development of a tool for automated coding that has the potential for broad impact.