Optical flow using opencv

Question

I am using Pyramid Lukas Kanade function of OpenCV to estimate the optical flow. i call the cvGoodFeaturesToTrack and then cvCalcOpticalFlowPyrLK . This is my code:

while(1)
{
...

cvGoodFeaturesToTrack(frameAth,eig_image,tmp_image,cornersA,&corner_count,0.01,5,NULL,3,0.4);

std::cout<<"CORNER COUNT AFTER GOOD FEATURES2TRACK CALL = "<<corner_count<<std::endl;

cvCalcOpticalFlowPyrLK(frameAth,frameBth,pyrA,pyrB,cornersA,cornersB,corner_count,cvSize(win_size,win_size),5,features_found,features_errors,cvTermCriteria( CV_TERMCRIT_ITER| CV_TERMCRIT_EPS,20,0.3 ),CV_LKFLOW_PYR_A_READY|CV_LKFLOW_PYR_B_READY);

cvCopy(frameBth,frameAth,0);
...
}

frameAth is the previous gray frame and frameBth is the current gray frame from a webcam. But when i output the number of good features to track in each frame the number decreases after sum time and keeps decreasing. but if i terminate the program and execute the code again(without disturbing the field of view of the webcam ) a lot more number of points are shown as good features to track...how can for the same field of view and for the same scene the function give such difference in number of points...and the difference is high..eg..number of points as good features to track after 4 minutes of execution is 20 or 50...but when the same program terminated and executed again the number is 500 to 700 initialy but again slowly decreases..i am using opencv for the past 4 months so i am lil new to openCV..please guide me or tell me where i can find a solution...lots of thanx in advance..

Answer 1

You have to call cvGoodFeaturesToTrack once (at the beginning, before loop) to detect good features to track and than track these features using cvCalcOpticalFlowPyrLK . Take a look at default opencv example: OpenCV/samples/cpp/lkdemo.cpp .

Answer 2

You are calling cvGoodFeatureToTrack and passing corner_count by reference. Its value decreases if less features are found. You have to reset the value of corner_count to its initial value before calling cvGoodFeaturesToTrack in each iteration of while loop.