Analysis on Affect Recognition Methods in the Wild

Karishma Raut, Sujata Kulkarni
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Abstract

Affect recognition transition from laboratory-controlled to challenging in the wild conditions is an intense area of research, with a potentially long list of important application. Audio-visual modalities are significant contributors that provide rich contextual information from real world challenging corpora. These modalities can be explored for better discrimination of real world human emotions that are complex and compound. A comprehensive literature survey is carried out to identify the most relevant big databases and the way features are extracted and fused from visual and auditory data. The main focus is on recent state of Art research work using real-world corpora and the work comparing designed framework on controlled as well as in the wild data.
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野外情感识别方法分析
影响识别从实验室控制到具有挑战性的野外条件的转变是一个激烈的研究领域,具有潜在的一长串重要应用。视听模式是提供来自现实世界具有挑战性的语料库的丰富上下文信息的重要贡献者。这些模式可以用于更好地辨别现实世界中复杂和复合的人类情感。进行了全面的文献调查,以确定最相关的大数据库以及从视觉和听觉数据中提取和融合特征的方式。主要关注的是最近使用真实世界语料库的最新研究工作,以及在受控数据和野生数据上比较设计框架的工作。
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