Assessing facial nerve function from visible facial signs such as resting asymmetry and symmetry of voluntary movement is an important means in clinical practice. By using image processing, computer vision and machine learning techniques, replacing the clinician with a machine to do assessment from ubiquitous visual face capture is progressing more closely to reality. This approach can do assessment in a purely automated manner, hence opens a promising direction for future development in this field. Many studies gathered around this interesting topic with a variety of solutions proposed in recent years. However, to date, none of these solutions have gained a widespread clinical use. This study provides a comprehensive review of the most relevant and representative studies in automated facial nerve function assessment from visual face capture, aiming at identifying the principal challenges in this field and thus indicating directions for future work.

中文翻译：

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视觉面部捕捉对自动面部神经功能评估的综述

从可见的面部征象评估面部神经功能，例如静止不对称和自发运动的对称性，是临床实践中的重要手段。通过使用图像处理，计算机视觉和机器学习技术，用机器代替临床医生从无处不在的视觉面部捕捉中进行评估的过程越来越接近现实。这种方法可以以纯自动化的方式进行评估，因此为该领域的未来发展打开了一个有希望的方向。近年来，围绕这一有趣的话题进行了许多研究，并提出了各种解决方案。但是，迄今为止，这些解决方案均未获得广泛的临床应用。这项研究从视觉面部捕捉，自动面部神经功能评估中最相关，最具代表性的研究进行了全面回顾，