【摘要】 视觉情感分析的目的是使用带有主观感情色彩的方式表述图像和视频,并使计算机能够检测和表达这些信息。伴随着社会化媒体的兴盛和充沛训练数据的出现,深度学习之类的技术革命给该领域带来新的机遇和挑战。从视觉情感语义提取框架出发,对传统视觉情感分析中视觉特征提取、情感空间建立和特征与情感的映射等关键技术进行综述;并对基于中间表达层、目标对象检测的视觉情感分析以及大数据背景下深度学习技术在该领域的应用进行论述;最后对视觉情感分析存在的问题进行总结并对未来有前景的研究方向进行展望。更多还原

【Abstract】 Visual sentiment analysis intends to describe images and videos in a subjective and emotional way and to detect and express the information with computers. With the emergence of social media and the rise of plenty of training data,technological revolution like deep learning has brought new opportunities and challenges into this field. This paper reviewed the key technologies including visual feature extraction,emotional space construction and mapping from visual features to emotion in traditional visual sentiment analysis on the basis of the framework for visual emotional semantic extraction. Then it discussed visual sentiment analysis based on middle representation and object detection and the application of deep learning in visual sentiment analysis under the background of big data. Finally it summarized the existing problems of visual sentiment analysis and gave inspirational future research directions.更多还原