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面部表情识别(FER)研究:愿景、架构要素及未来方向

Facial expression recognition (FER) survey: a vision, architectural elements, and future directions.

作者信息

Ullah Sana, Ou Jie, Xie Yuanlun, Tian Wenhong

机构信息

School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.

出版信息

PeerJ Comput Sci. 2024 Jun 3;10:e2024. doi: 10.7717/peerj-cs.2024. eCollection 2024.

Abstract

With the cutting-edge advancements in computer vision, facial expression recognition (FER) is an active research area due to its broad practical applications. It has been utilized in various fields, including education, advertising and marketing, entertainment and gaming, health, and transportation. The facial expression recognition-based systems are rapidly evolving due to new challenges, and significant research studies have been conducted on both basic and compound facial expressions of emotions; however, measuring emotions is challenging. Fueled by the recent advancements and challenges to the FER systems, in this article, we have discussed the basics of FER and architectural elements, FER applications and use-cases, FER-based global leading companies, interconnection between FER, Internet of Things (IoT) and Cloud computing, summarize open challenges in-depth to FER technologies, and future directions through utilizing Preferred Reporting Items for Systematic reviews and Meta Analyses Method (PRISMA). In the end, the conclusion and future thoughts are discussed. By overcoming the identified challenges and future directions in this research study, researchers will revolutionize the discipline of facial expression recognition in the future.

摘要

随着计算机视觉的前沿进展,面部表情识别(FER)因其广泛的实际应用而成为一个活跃的研究领域。它已被应用于各个领域,包括教育、广告与营销、娱乐与游戏、健康和交通。基于面部表情识别的系统由于新的挑战而迅速发展,并且已经针对基本情绪和复合情绪的面部表情开展了大量研究;然而,测量情绪具有挑战性。受FER系统近期进展和挑战的推动,在本文中,我们讨论了FER的基础知识和架构要素、FER应用及用例、基于FER的全球领先公司、FER与物联网(IoT)和云计算之间的互连,深入总结了FER技术面临的开放挑战,以及通过利用系统评价与荟萃分析的首选报告项目(PRISMA)得出的未来方向。最后,讨论了结论和未来展望。通过克服本研究中确定的挑战和未来方向,研究人员将在未来彻底改变面部表情识别学科。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd40/11157619/92aa1fdee35a/peerj-cs-10-2024-g001.jpg

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