Automatic Analysis of Facial Actions: A Survey
Automatic Analysis of Facial Actions: A Survey
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DOI：
10.1109/taffc.2017.2731763
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发表时间：
2019-07-01
影响因子：
11.2
通讯作者：
Pantic, Maja
中科院分区：
文献类型：
--
作者：
Martinez, Brais;Valstar, Michel F.;Pantic, Maja
面部动作编码系统（FACS）作为描述面部表情最全面、最客观的方法之一，近年来受到了广泛的关注。在过去的30年里，心理学家和神经科学家利用FACS对面部表情分析的各个方面进行了广泛的研究。自动化FACS编码将使这项研究更快、更广泛地适用，为理解我们如何通过面部表情进行交流开辟了新的途径。这样的自动化过程还可以潜在地提高编码的可靠性、精度和时间分辨率。本文对面部动作的机器分析研究进行了全面的综述。我们系统地回顾了这些系统的所有组成部分：预处理，特征提取和面部动作的机器编码。此外，对现有facs编码的面部表情数据库进行了总结。最后，广泛讨论了使面部动作自动分析应用于现实生活中所面临的挑战。我们写这篇调查论文有两个潜在的动机：第一是对现有文献进行最新的回顾，第二是对面部动作的机器识别的未来提供一些见解：该领域的研究人员面临的挑战和机遇是什么。
As one of the most comprehensive and objective ways to describe facial expressions, the Facial Action Coding System (FACS) has recently received significant attention. Over the past 30 years, extensive research has been conducted by psychologists and neuroscientists on various aspects of facial expression analysis using FACS. Automating FACS coding would make this research faster and more widely applicable, opening up new avenues to understanding how we communicate through facial expressions. Such an automated process can also potentially increase the reliability, precision and temporal resolution of coding. This paper provides a comprehensive survey of research into machine analysis of facial actions. We systematically review all components of such systems: pre-processing, feature extraction and machine coding of facial actions. In addition, the existing FACS-coded facial expression databases are summarised. Finally, challenges that have to be addressed to make automatic facial action analysis applicable in real-life situations are extensively discussed. There are two underlying motivations for us to write this survey paper: the first is to provide an upto-date review of the existing literature, and the second is to offer some insights into the future of machine recognition of facial actions: what are the challenges and opportunities that researchers in the field face.