情绪检测数据集

Question

我正在使用opencv库编写代码,该库跟踪用户的脸部和脸部的特征.我已经设法对网络进行实时检测以及来自网络摄像头的眼睛,嘴唇等功能.我现在想从检测到的特征中提取情绪.我想知道是否有任何可用的数据集,我可以用它来比较情绪和如何做.

这是面部检测的代码

    CvRect detectFaceInImage(const IplImage *inputImg, const CvHaarClassifierCascade* cascade )
{
    const CvSize minFeatureSize = cvSize(20, 20);
    const int flags = CV_HAAR_FIND_BIGGEST_OBJECT | CV_HAAR_DO_ROUGH_SEARCH;    // Only search for 1 face.
    const float search_scale_factor = 1.1f;
    IplImage *detectImg;
    IplImage *greyImg = 0;
    CvMemStorage* storage;
    CvRect rc;
    double t;
    CvSeq* rects;
    int i;

    storage = cvCreateMemStorage(0);
    cvClearMemStorage( storage );

    // If the image is color, use a greyscale copy of the image.
    detectImg = (IplImage*)inputImg;    // Assume the input image is to be used.
    if (inputImg->nChannels > 1) 
    {
        greyImg = cvCreateImage(cvSize(inputImg->width, inputImg->height), IPL_DEPTH_8U, 1 );
        cvCvtColor( inputImg, greyImg, CV_BGR2GRAY );
        detectImg = greyImg;    // Use the greyscale version as the input.
    }

    // Detect all the faces.
    t = (double)cvGetTickCount();
    rects = cvHaarDetectObjects( detectImg, (CvHaarClassifierCascade*)cascade, storage,
                search_scale_factor, 3, flags, minFeatureSize );
    t = (double)cvGetTickCount() - t;
    printf("[Face Detection took %d ms and found %d objects]\n", cvRound( t/((double)cvGetTickFrequency()*1000.0) ), rects->total );

    // Get the first detected face (the biggest).
    if (rects->total > 0) {
        rc = *(CvRect*)cvGetSeqElem( rects, 0 );
    }
    else
        rc = cvRect(-1,-1,-1,-1);   // Couldn't find the face.

    //cvReleaseHaarClassifierCascade( &cascade );
    //cvReleaseImage( &detectImg );
    if (greyImg)
        cvReleaseImage( &greyImg );
    cvReleaseMemStorage( &storage );

    return rc;  // Return the biggest face found, or (-1,-1,-1,-1).
}

Answer 1

我正在使用Karolinska Directed Emotional Faces(KDEF)照片进行教育研究项目.有关数据集的信息,请访问http://www.emotionlab.se/resources/kdef.

请注意,您可能需要裁剪,调整大小,居中,拉直和规范化图像,以便将它们与OpenCV一起使用.一旦正确准备,图像与所有OpenCV2 FaceRecognizer类函数一起工作得很好.

至于如何进行面部表情识别:不存在标准方法.首先阅读FaceRecognizer文档并完成教程.值得一提的是:我发现使用局部二值模式直方图可以得到最准确的结果.