摘要
为了合理地表示和自动识别电影情感内容,解决电影情感语义理解中存在的"情感鸿沟"难题,提出一种面向观众的个性化电影情感空间建模方法.采用模糊c-均值聚类算法划分诱力-激励情感空间,并利用高斯混合模型定义划分得到的模糊情感子空间的情感隶属度函数,使得模糊情感子空间的中心、边界、形状和密度可以真实地反映观众欣赏视频节目时的个性化信息;设计并提取了2组电影情感特征向量,采用多层感知机和多元线性回归计算它们的情感坐标.基于情感坐标和情感隶属度函数引入"最大隶属原则"和"阈值原则",以便表示和识别观众观影过程中的个性化情感体验.实验结果表明,该方法能够有效地表示和识别个性化电影情感内容.
In order to represent and recognize the movie affective content reasonably and automatically,an audience oriented personalized movie emotion space modeling method is proposed as a solution for the ＂affective gap＂.It is an essential problem on the movie affective semantic understanding.By our method,a fuzzy c-mean clustering（FCM） algorithm is adopted to divide the Valence-Arousal emotion space into the typical fuzzy emotion subspaces and Gaussian mixture model（GMM） is used to determine their affective membership functions.The centers,borders,shapes and densities of these subspaces can truthfully reflect the emotional tendencies of audiences.Two sets of movie affective feature vectors are formulated.Multi-layer perception（MLP） and multiple linear regression are adopted to compute the emotion coordinates of these movie affective feature vectors.Based on the affective membership functions and emotion coordinates,the maximum membership principle and the threshold principle are introduced to represent and recognize the emotional preferences of the audiences.Experimental results demonstrate that the proposed modeling method can be applied to effectively represent and recognize the personalized movie affective content.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第1期136-144,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60703049)
湖北省自然科学基金(2007ABA265)
武汉市青年科技晨光计划(200850731353)
关键词
情感内容
情感空间
特征向量
情感坐标
affective content emotion space feature vector emotion coordinate
