Automatic depression assessment based on visual cues is a rapidly growing research domain. The present exhaustive review of existing approaches as reported in over sixty publications during the last ten years focuses on image processing and machine learning algorithms. Visual manifestations of depression, various procedures used for data collection, and existing datasets are summarized. The review outlines methods and algorithms for visual feature extraction, dimensionality reduction, decision methods for classification and regression approaches, as well as different fusion strategies. A quantitative meta-analysis of reported results, relying on performance metrics robust to chance, is included, identifying general trends and key unresolved issues to be considered in future studies of automatic depression assessment utilizing visual cues alone or in combination with vocal or verbal cues.

中文翻译：

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基于视觉线索的抑郁自动评估：系统评价

基于视觉线索的自动抑郁症评估是一个快速发展的研究领域。目前对过去十年中六十多份出版物中报道的现有方法的详尽审查侧重于图像处理和机器学习算法。总结了抑郁症的视觉表现、用于数据收集的各种程序和现有数据集。该评论概述了视觉特征提取、降维、分类和回归方法的决策方法以及不同的融合策略的方法和算法。包括对报告结果的定量元分析，依赖于对机会稳健的绩效指标，包括，