模版匹配

vector<TemplateMatchModes> methods = {TM_SQDIFF,TM_SQDIFF_NORMED,TM_CCORR,TM_CCORR_NORMED,TM_CCOEFF,TM_CCOEFF_NORMED};
for (int i=0;i<methods.size();i++) {
    TemplateMatchModes method = methods[i];
    frame.copyTo(f1);
    matchTemplate(f1, head, f2, method);
    double minVal,maxVal;
    cv::Point minLoc,maxLoc;
    minMaxLoc(f2, &minVal, &maxVal, &minLoc, &maxLoc);
    cv::Point topLeft,bottomRight;
    if (method<=TM_SQDIFF_NORMED) {
        topLeft = minLoc;
    }else{
        topLeft = maxLoc;
    }
    bottomRight = {topLeft.x+head.cols,topLeft.y+head.rows};
    rectangle(frame, topLeft, bottomRight, Scalar(255,255,255,255),5);
}

类型	同照片	异照片	其他
TM_SQDIFF
TM_SQDIFF_NORMED
TM_CCORR
TM_CCORR_NORMED
TM_CCOEFF
TM_CCOEFF_NORMED

TM_SQDIFF , TM_SQDIFF_NORMED, TM_CCORR_NORMED效果都还行，都识别到位了 (这里不是特征识别，识别的不是常规人脸，所以只对相似特征识别）

这里有这几种算法的说明
https://blog.csdn.net/coroutines/article/details/78229105

查找多个匹配

TemplateMatchModes method = TM_CCOEFF_NORMED;
float threshold = 0.9;
frame.copyTo(f1);
matchTemplate(f1, head, f2, method);
cv::threshold(f2, f2, threshold-.05, 1, THRESH_TOZERO);
double minVal,maxVal;
cv::Point minLoc,maxLoc;

while (true) {
    minMaxLoc(f2, &minVal, &maxVal, &minLoc, &maxLoc);
    if (maxVal > threshold){
        NSLog(@"Matched %f %f",minLoc.x, minLoc.y);
        rectangle(
                  frame,
                  maxLoc,
                  cv::Point(maxLoc.x + head.cols, maxLoc.y + head.rows),
                  CV_RGB(0,255,0), 10
                  );
        floodFill(f2, maxLoc, cv::Scalar(0), 0, cv::Scalar(.1), cv::Scalar(1.));
    }else{
        NSLog(@"No More Matches");
        break;
    }
}   

需要使用TM_CCOEFF_NORMED， 并且遍历的原理是把已找到结果的数据图填补上，让结果刷新。貌似没有找到旋转后的图像

image.png

8448418_152411419000_2.jpg