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标 题: A Personalized Emotion Space for Video Affective Content Representation
作 者: Kai Sun,Yu Junqing, Huang Yue, Hu Xiaoqiang
会议 / 期刊: Wuhan University Journal of Natural Sciences, 14(5):393-398
发 表 时 间: 2009年
下 载 地 址: 暂不提供下载
论文摘要
A personalized emotion space is proposed to bridge the “affective gap” in video affective content understanding. In order to u
nify the discrete and dimensional emotion model, fuzzy C-mean (FCM) clustering algorithm is adopted to divide the emotion space.
Gaussian mixture model (GMM) is used to determine the membership functions of typical affective subspaces. At every step of model
ing the space, the inputs rely completely on the affective experiences recorded by the audiences. The advantages of the improved
V-A(Velance-Arousal) emotion model are the personalization, the ability to define typical affective state areas in the V-A emotio
n space, and the convenience to explicitly express the intensity of each affective state. The experimental results validate the m
odel and show it can be used as a personalized emotion space for video affective content representation

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