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标 题: An Improved Valence-Arousal Emotion Space for Video Affective Content Representation and Recognition
作 者: Kai Sun, Junqing Yu, Yue Huang, Xiaoqiang Hu
会议 / 期刊: Proceedings of IEEE International Conference on Multimedia and Expo, 266-569(EI
发 表 时 间: 2009年
下 载 地 址: 点击下载
论文摘要
To understand video affective content automatically, the primary task is to transform the abstract concept of emotion into the fo
rm which can be handled by the computer easily.An improved V-A emotion space is proposed to address this
problem. It unifies the discrete and dimensional emotion model by introducing the typical fuzzy emotion subspace.Fuzzy C-mean clu
stering (FCM) algorithm is adopted to divide the V-A emotion space into the subspaces and Gaussian mixture model (GMM) is used to
determine their membership functions. Based on the proposed emotion space, the maximum membership principle and the threshold pr
inciple are introduced to represent and recognize video affective content. A video affective content database is created to valid
ate the proposed model. The experimental results show that the improved emotion space can be used as a solution to represent and
recognize video affective content.

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