Here is another way to use the feature detectors. Instead of using the general FeatureDetector interface, here each feature-detector class is called individually and the associated functions are called.
[code lang=”cpp”]
int main(int argc, char* argv[]){
cv::VideoCapture cam("D:/Pictures/20120811_140513.mp4");
cv::Mat frames;
cv::Mat grayIm;
double FPS=0.;
double FPS_sum = 0.;
int FPS_count = 0;
long prevTick = 0;
int count = 0;
char str[256] ={‘\0’};
std::vector<cv::KeyPoint> keyp;
if(!cam.isOpened())
return -1;
cam>>frames;
grayIm.create(frames.rows,frames.cols,frames.type());
cv::SURF detector;
while(cv::waitKey(1)!=27){
cam>>frames;
cv::resize(frames,frames,cv::Size(),0.5,0.5);
cv::cvtColor(frames,grayIm,CV_RGB2GRAY);
detector.detect(grayIm,keyp);
for(int i=0;i<keyp.size();i++)
cv::circle(frames,cv::Point(keyp[i].pt.x,keyp[i].pt.y),2,cv::Scalar(255,0,0,255));
if(count==0){
int currenttick = cv::getTickCount();
FPS = cv::getTickFrequency()/(currenttick – prevTick)*30;
if(FPS_count!=0) FPS_sum += FPS;
FPS_count++;
prevTick = cv::getTickCount();
}
count = ++count % 30;
sprintf(str,"FPS = %0.2f\0",FPS);
cv::putText(frames,str,cv::Point(20,50),CV_FONT_HERSHEY_SIMPLEX,1,cv::Scalar(255,0,255,0));
cv::imshow("Camera",frames);
cout<<"Average FPS = "<<FPS_sum/(FPS_count-1)<<std::endl;
}
return 0;
}
[/code]
Input and platform: same as the previous one
Results:
| Name | FPS |
| FREAK | 31.6729 – Does Not Track Anything |
| GFTTDetector | Extremely slow – one frame takes about a minute |
| MSER | 1.299 |
| SIFT (in Nonfree Module) | 1.637 |
| SURF (in Nonfree Module) | 0.981 |