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Hybrid deep learning method for recognizing facial expressions

机译:混合深度学习的面部表情识别方法

摘要

A computer implemented method for recognizing facial expressions by applying feature learning and feature engineering to face images. The method includes conducting feature learning on a face image comprising feeding the face image into a first convolution neural network to obtain a first decision, conducting feature engineering on a face image, comprising the steps of automatically detecting facial landmarks in the face image, transforming the facial features into a two-dimensional matrix, and feeding the two-dimensional matrix into a second convolution neural network to obtain a second decision, computing a hybrid decision based on the first decision and the second decision, and recognizing a facial expression in the face image in accordance to the hybrid decision.
机译:一种通过将特征学习和特征工程应用于面部图像来识别面部表情的计算机实现的方法。该方法包括对面部图像进行特征学习,包括将面部图像馈送到第一卷积神经网络以获得第一决策;对面部图像进行特征工程,包括自动检测面部图像中的面部界标,对面部图像进行变换的步骤。将面部特征转换成二维矩阵,然后将二维矩阵输入第二个卷积神经网络以获得第二个决策,然后根据第一个决策和第二个决策计算混合决策,并识别面部表情图像按照混合决策。

著录项

  • 公开/公告号US2020293755A1

    专利类型

  • 公开/公告日2020-09-17

    原文格式PDF

  • 申请/专利权人 SHUTTERFLY LLC;

    申请/专利号US202016890309

  • 发明设计人 LEO CYRUS;

    申请日2020-06-02

  • 分类号G06K9;G06N3/08;G06K9/62;

  • 国家 US

  • 入库时间 2022-08-21 11:26:21

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