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Is a picture worth 1000 votes? Analyzing the sentiment of election related social photos

机译：一张价值1000票的图片吗？分析选举相关社会照片的情绪

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摘要

This paper explores techniques for automatically recognizing the sentiment of facial expressions in social photos, especially those of politicians in the context of elections. We first use the Active Shape Model (ASM) to extract facial feature points. Next, the shape model points from the ASM are normalized to a standard shape and then submitted to a trained AdaBoost classifier to recognize the sentiment of facial expressions. Three types of sentiment are of primary interest: flattering, neutral and unflattering. Finally, the approach is evaluated by experiments, which indicate that the proposed method is sufficiently effective for facial expression analysis of images of election candidates and thus can be used to gauge the public opinion during the election.
机译：本文探讨了自动识别社会照片中面部表情情绪的技术，特别是政治家在选举范围内的情绪。我们首先使用活动形状模型（ASM）提取面部特征点。接下来，来自ASM的形状模型点被标准化为标准形状，然后提交给培训的Adaboost分类器以识别面部表情的情文。三种情绪是主要的兴趣：讨人喜欢，中立和不普通的。最后，通过实验评估该方法，表明该方法对于选举候选人的图像的面部表达分析是足够有效的，因此可用于在选举中衡量舆论。

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