Facial expressions are an ideal means of communicating one's emotions or intentions to others. This overview will focus on human facial expression recognition as well as robotic facial expression generation. In case of human facial expression recognition, both facial expression recognition on predefined datasets as well as in real time will be covered. For robotic facial expression generation, hand coded and automated methods i.e., facial expressions of a robot are generated by moving the features (eyes, mouth) of the robot by hand coding or automatically using machine learning techniques, will also be covered. There are already plenty of studies that achieve high accuracy for emotion expression recognition on predefined datasets, but the accuracy for facial expression recognition in real time is comparatively lower. In case of expression generation in robots, while most of the robots are capable of making basic facial expressions, there are not many studies that enable robots to do so automatically.
翻译:面部表达方式是将一个人的情感或意图传递给他人的一种理想手段。 概览将侧重于人类面部表达表达方式识别以及机器人面部表达表达方式生成。 在人类面部表达方式识别方面, 将覆盖预先定义的数据集和实时的面部表达方式识别。 对于机器人面部表达方式的生成, 手动编码和自动方法, 即机器人的面部表达方式是通过手动编码或自动使用机器学习技术移动机器人的特征( 眼部、 口部) 生成的, 也将包含在内。 已经有许多研究在预定义的数据集中实现情感表达表达方式识别的高度准确性, 但实时面部表达方式识别的准确性相对较低。 在机器人的面部表达方式生成方面, 虽然大多数机器人能够进行基本的面部表达方式, 但没有很多研究使机器人能够自动进行这种表达。