Comics are complex documents whose reception engages cognitive processes such as scene perception, language processing, and narrative understanding. Possibly because of their complexity, they have rarely been studied in cognitive science. Modeling the stimulus ideally requires a formal description, which can be provided by feature descriptors from computer vision and computational linguistics. With a focus on document analysis, here we review work on the computational modeling of comics. We argue that the development of modern feature descriptors based on deep learning techniques has made sufficient progress to allow the investigation of complex material such as comics for reception studies, including experimentation and computational modeling of cognitive processes.

中文翻译：

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漫画分析的计算方法。

漫画是复杂的文档，其接收涉及诸如场景感知，语言处理和叙述理解之类的认知过程。可能由于它们的复杂性，很少在认知科学中对其进行研究。理想情况下，对刺激进行建模需要正式的描述，该描述可以由计算机视觉和计算语言学的特征描述符提供。着重于文档分析，在这里我们回顾关于漫画的计算建模的工作。我们认为，基于深度学习技术的现代特征描述符的开发已经取得了足够的进展，可以研究复杂的材料，例如用于接受研究的漫画，包括认知过程的实验和计算模型。