The current challenges of automatic recognition of facial expressions: A systematic review

IF 1.4 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

AI Communications Pub Date : 2020-09-22 DOI:10.3233/aic-200631

Audrey Masson, Guillaume Cazenave, Julien Trombini, M. Batt

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引用次数: 5

Abstract

In recent years, due to its great economic and social potential, the recognition of facial expressions linked to emotions has become one of the most flourishing applications in the field of artificial intelligence, and has been the subject of many developments. However, despite significant progress, this field is still subject to many theoretical debates and technical challenges. It therefore seems important to make a general inventory of the different lines of research and to present a synthesis of recent results in this field. To this end, we have carried out a systematic review of the literature according to the guidelines of the PRISMA method. A search of 13 documentary databases identified a total of 220 references over the period 2014–2019. After a global presentation of the current systems and their performance, we grouped and analyzed the selected articles in the light of the main problems encountered in the field of automated facial expression recognition. The conclusion of this review highlights the strengths, limitations and main directions for future research in this field.

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面部表情自动识别当前面临的挑战:系统综述

近年来，由于其巨大的经济和社会潜力，与情绪相关的面部表情识别已成为人工智能领域最蓬勃的应用之一，并已成为许多发展的主题。然而，尽管取得了重大进展，该领域仍然受到许多理论争论和技术挑战。因此，似乎重要的是对不同的研究方向进行一般性的盘点，并综合这一领域的最新成果。为此，我们根据PRISMA方法的指导原则对文献进行了系统的综述。通过对13个文献数据库的检索，在2014-2019年期间共确定了220篇参考文献。在全面介绍了当前系统及其性能之后，我们根据自动面部表情识别领域遇到的主要问题对所选文章进行了分组和分析。本文总结了该领域的优势、局限性和未来研究的主要方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

AI Communications 工程技术-计算机：人工智能

CiteScore

2.30

自引率

12.50%

发文量

审稿时长

4.5 months

期刊介绍： AI Communications is a journal on artificial intelligence (AI) which has a close relationship to EurAI (European Association for Artificial Intelligence, formerly ECCAI). It covers the whole AI community: Scientific institutions as well as commercial and industrial companies. AI Communications aims to enhance contacts and information exchange between AI researchers and developers, and to provide supranational information to those concerned with AI and advanced information processing. AI Communications publishes refereed articles concerning scientific and technical AI procedures, provided they are of sufficient interest to a large readership of both scientific and practical background. In addition it contains high-level background material, both at the technical level as well as the level of opinions, policies and news.