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Facial emotional recognition apparatus for Identify Emotion and method thereof

机译:用于识别情绪的面部情绪识别装置及其方法

摘要

The present invention relates to a facial emotion recognition apparatus for distinguishing emotion from an input facial image and a method thereof. According to the present invention, the facial emotion recognition apparatus comprises: a facial feature extraction unit receiving the facial image from which the emotion is distinguished, extracting features of the entire facial image from the inputted facial image, and transferring information about two high-ranking emotions among acquired six emotions from the extracted features; a geometric variance extraction unit comparing feature points assigned to the inputted facial image with feature points assigned to a default facial image with respect to the same person to extract a coordinate difference and applying a coordinate difference value to a CNN algorithm to calculate vector values of the two high-ranking emotions; and an emotion classification unit assigning weight to an emotion recognition value extracted from the facial feature extraction unit and the vector values calculated in the geometric variance extraction unit to classify the emotion having the highest value among calculated result values as a final emotion. Accordingly, the facial emotion recognition apparatus corrects an emotion recognition error frequently generated from two high-ranking emotions acquired through an existing algorithm and assigns the weight to the emotion recognition value extracted from the facial features and the vector values calculated from geometric variances to calculate a result value, thereby providing an effect of determining the final emotion with increased correctness.
机译:面部情绪识别装置及其方法技术领域本发明涉及一种用于从输入的面部图像中区分情绪的面部情绪识别装置及其方法。根据本发明,面部表情识别装置包括:面部特征提取单元,其接收从中区分出情感的面部图像;从输入的面部图像中提取整个面部图像的特征;以及传送关于两个高级的信息。从提取的特征中获得的六种情绪中的情绪;几何方差提取单元,针对同一人,将分配给输入的面部图像的特征点与分配给默认面部图像的特征点进行比较,以提取坐标差,并将坐标差值应用于CNN算法,以计算坐标的差值。两种高级情感;情感分类单元将权重分配给从面部特征提取单元提取的情感识别值和在几何方差提取单元中计算出的矢量值,以将计算结果值中具有最高值的情感分类为最终情感。因此,面部情感识别设备校正由通过现有算法获取的两个高级情感经常产生的情感识别错误,并将权重分配给从面部特征提取的情感识别值和根据几何方差计算的矢量值,以计算结果值,从而提供确定正确性更高的最终情感的效果。

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