面部表情
表达式(计算机科学)
情绪识别
计算机科学
集合(抽象数据类型)
情绪分类
面部表情识别
人工智能
钥匙(锁)
图像(数学)
模式识别(心理学)
自然语言处理
机器学习
语音识别
面部识别系统
计算机安全
程序设计语言
作者
Ying Zhou,Xue Hui-feng,Xin Geng
标识
DOI:10.1145/2733373.2806328
摘要
Most existing facial expression recognition methods assume the availability of a single emotion for each expression in the training set. However, in practical applications, an expression rarely expresses pure emotion, but often a mixture of different emotions. To address this problem, this paper deals with a more common case where multiple emotions are associated to each expression. The key idea is to learn the specific description degrees of all basic emotions for each expression and the mapping from the expression images to the emotion distributions by the proposed emotion distribution learning (EDL) method.The databases used in the experiments are the s-JAFFE database and the s-BU\_3DFE database as they are the databases with explicit scores for each emotion on each expression image. Experimental results show that EDL can effectively deal with the emotion distribution recognition problem and perform remarkably better than the state-of-the-art multi-label learning methods.
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