图书情报知识 ›› 2020, Vol. 0 ›› Issue (3): 119-127.doi: 10.13366/j.dik.2020.03.119

• 情报、信息与共享 • 上一篇    下一篇

图片情感分析研究综述

王仁武,孟现茹   

  • 出版日期:2020-05-10 发布日期:2020-05-21

Review of Image Sentiment Analysis

  • Online:2020-05-10 Published:2020-05-21

摘要: [目的/意义]基于图片的情感分析已逐渐成为情感分析的潜在研究热点。本文回顾与总结了图片情感分析的历史与现状,有助于相关研究工作的推进。[研究设计/方法]从传统的视觉情感分析方法和深度学习两个方向对图片情感分析相关研究的技术方法进行梳理并评述。[结论/发现] 随着图片情感分析粒度的细化,进一步的研究方向在于深度学习算法和标注方式的优化;同时,加快带有情感标签图片数据集的开放进程,可以更好地推动研究者在此领域研究的不断深入。[创新/价值]深入梳理了图片情感分析现阶段的研究重点与未来发展方向,为该领域进一步研究提供相关借鉴。

关键词: 图片情感分析, 视觉特征提取, 图像标注, 深度学习

Abstract: [Purpose/Significance]Image-based sentiment analysis has gradually become a potential research hotspot. This paper intends to make a summary on the history and current situation of image sentiment analysis, which could be beneficial to promote relevant research.[Design/Methodology]This paper reviewed and offered comments on the technical methods of image sentiment analysis from two dimensions including the traditional image sentiment analysis method and the deep learning method.[Findings/Conclusion]It has been found that with the refinement of image sentiment analysis granularity, the further research will focus on the optimization of deep learning algorithm and annotation. At the same time, accelerating the opening process of sentiment labelled data-sets could help researchers to do further research in this field.[Originality/Value]This paper conducts an in-depth summary on the emphasis and development direction of image sentiment analysis, which could provide some reference for further research in this field.

Key words: Image sentiment analysis, Visual feature extraction, Image annotation, Deep learning