基于图像的群体情绪识别综述
Survey on Group-level Emotion Recognition in Images
高帅鹏 1王怡凡1
作者信息
- 1. 中国石油大学(华东)计算机科学与技术学院,山东 青岛 266580
- 折叠
摘要
近年来,基于图像的群体情绪识别受到了广泛关注,其旨在准确判断不同场景不同数量人群下群体的整体情绪状态.由于群体情绪识别涉及图像中人脸情绪特征、场景特征、人体姿态特征等多种群体情绪线索的分析和融合,使得该领域十分具有挑战性.现阶段该领域缺少相关综述性的文章对现有的研究进行整理,从而更好地进行下一步的研究.本文对该领域内不同情绪线索和不同处理方式的群体情绪识别模型进行细致梳理和分类;同时回顾并分析现有模型的处理方法和特点,整理不同融合方式的模型以及该领域的主流数据库;最后,针对该领域的发展进行简要总结和展望.
Abstract
In recent years,image-based group emotion recognition has received widespread attention,which aims to accurately determine the overall emotional state of groups in different scenes and with different numbers of people.Since group emotion rec-ognition involves the analysis and fusion of multiple group emotion clues such as facial emotional features,scene features,and human posture features in pictures,this field is very challenging.At this stage,there is a lack of relevant review articles in this field to sort out the existing research,so as to better conduct the next step of research.This article carefully sorts out and catego-rizes group emotion recognition models with different emotional cues and different processing methods in this field.At the same time,the processing methods and characteristics of existing models are reviewed and analyzed,and models with different fusion methods and mainstream databases in this field are sorted out.Finally,a brief summary and outlook on the development of this field are given.
关键词
群体情绪识别/深度学习/卷积神经网络/注意力机制Key words
group-level emotion recognition/deep learning/convolutional neural network/attention mechanism引用本文复制引用
基金项目
山东省自然科学基金资助项目(ZR202211180156)
出版年
2024
国家科技期刊平台
NSTL
万方数据