基于深度学习卷积神经网络实现的人脸面部表情识别系统项目源代码.zip

上传者: 55305220 | 上传时间: 2022-06-11 09:09:48 | 文件大小: 12.18MB | 文件类型: ZIP
主要功能 (1)可以通过从本地图片导入系统,或者直接相机进行拍摄等方法对图片和视频进行处理并分析。 (2)可以切换模型对图片进行处理。 实现原理 (1)表情库的建立 目前,研究中比较常用的表情库主要有:美国CMU机器人研究所和心理学系共同建立的Cohn-Kanade AU-Coded Facial Expression Image Database(简称CKACFEID)人脸表情数据库;fer2013人脸数据集等等,这里我们的系统采用fer2013人脸数据集。 (2)表情识别: ①图像获取:通过摄像头等图像捕捉工具获取静态图像或动态图像序列。 ②图像预处理:图像的大小和灰度的归一化,头部姿态的矫正,图像分割等。(改善图像质量,消除噪声,统一图像灰度值及尺寸,为后序特征提取和分类 识别打好基础) (3)特征提取:将点阵转化成更高级别图像表述—如形状、运动、颜色、纹理、空间结构等,?在尽可能保证稳定性和识别率的前提下,对庞大的图像数据进 行降维处理。 (4)基于运动特征的提取:提取动态图像序列的运动特征 (5)分类判别:包括设计和分类决策(在表情识别的分类器设计和选择阶段,主要有以下方法:

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