Visual Sentiment Analysis aims to understand how images affect people, in terms of evoked emotions. Although this field is rather new, a broad range of techniques have been developed for various data sources and problems, resulting in a large body of research. This paper reviews pertinent publications and tries to present an exhaustive overview of the field. After a description of the task and the related applications, the subject is tackled under different main headings. The paper also describes principles of design of general Visual Sentiment Analysis systems from three main points of view: emotional models, dataset definition, feature design. A formalization of the problem is discussed, considering different levels of granularity, as well as the components that can affect the sentiment toward an image in different ways. To this aim, this paper considers a structured formalization of the problem which is usually used for the analysis of text, and discusses it's suitability in the context of Visual Sentiment Analysis. The paper also includes a description of new challenges, the evaluation from the viewpoint of progress toward more sophisticated systems and related practical applications, as well as a summary of the insights resulting from this study.

中文翻译：

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视觉情感分析调查

视觉情感分析旨在了解图像如何通过诱发的情感影响人。尽管该领域是一个相当新的领域，但是已经针对各种数据源和问题开发了广泛的技术，从而进行了大量的研究。本文对相关出版物进行了综述，并试图对该领域进行详尽的概述。在描述任务和相关应用之后，将在不同的主要标题下解决该主题。本文还从三个主要角度描述了通用视觉情感分析系统的设计原理：情感模型，数据集定义，特征设计。考虑到不同级别的粒度以及可能以不同方式影响图像情感的组件，讨论了问题的形式化问题。为此，本文考虑了通常用于文本分析的问题的结构化形式化，并讨论了它在视觉情感分析中的适用性。本文还包括对新挑战的描述，从朝着更复杂的系统和相关的实际应用的发展角度进行评估以及对本研究得出的见解的总结。