基于深度卷积神经网络实现的人脸表情识别系统源码+数据集+模型,基于Keras+OpenCv+PyQt5实现

上传者: 2301_76484015 | 上传时间: 2023-04-11 16:16:23 | 文件大小: 12.01MB | 文件类型: ZIP
介绍 基于深度卷积神经网络实现的人脸表情识别系统,系统程序由Keras, OpenCv, PyQt5的库实现,训练测试集采用fer2013表情库。 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

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