Fine-Grained Emotion Prediction for Movie and Television scene images

作     者：Su Zhibin Zhou Xuanye Liu Bing Ren Hui Su Zhibin;Zhou Xuanye;Liu Bing;Ren Hui

作者机构：State Key Laboratory of Media Convergence and CommunicationCommunication University of ChinaBeijing 100024China Key Laboratory of Acoustic Visual Technology and Intelligent Control SystemCommunication University of ChinaBeijing 100024China School of Information and Communication EngineeringCommunication University of ChinaBeijing 100024China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2024年第31卷第3期

页      面：43-55页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the Open Project of Key Laboratory of Audio and Video Restoration and Evaluation(2021KFKT005) 

主　　题：fine-grained emotion prediction movie and television scene images stacking model linear regression 

摘      要：For the task of content retrieval,analysis and generation of film and television scene images in the field of intelligent editing,fine-grained emotion recognition and prediction of images is of great *** this paper,the fusion of traditional perceptual features,art features and multi-channel deep learning features are used to reflect the emotion expression of different levels of the *** addition,the integrated learning model with stacking architecture based on linear regression coefficient and sentiment correlations,which is called the LS-stacking model,is proposed according to the factor association between multi-dimensional *** experimental results prove that the mixed feature and LS-stacking model can predict well on the 16 emotion categories of the self-built image *** study improves the fine-grained recognition ability of image emotion by computers,which helps to increase the intelligence and automation degree of visual retrieval and post-production system.