OpenCV goodFeaturesToTrack's status are zeros - c++

Question

Trying to implement Optical Flow for iOS with OpenCV 3.1 .
I built the basic stuff as shown in the below code and I do get features points from goodFeaturesToTrack but the thing is no point is being tracked, and status results are always zeros (not successfully tracked).
cv::Mat gray; // current gray-level image
cv::Mat gray_prev;
std::vector<cv::Point2f> features; // detected features
std::vector<cv::Point2f> newFeatures;
std::vector<uchar> status; // status of tracked features
std::vector<float> err; // error in tracking
cv::TermCriteria _termcrit = cv::TermCriteria(cv::TermCriteria::COUNT|cv::TermCriteria::EPS,20,0.03);
-(void)processImage:(cv::Mat&)image {
//-------------------- Optical Flow ---------------------
cv::cvtColor(image, gray, CV_BGR2GRAY);
if(gray_prev.empty()) {
gray.copyTo(gray_prev);
}
cv::goodFeaturesToTrack(gray, features, 20, 0.01, 10);
cv::calcOpticalFlowPyrLK(gray_prev, gray, features, newFeatures, status, err, cv::Size(10, 10), 3, _termcrit, 0, 0.001);
// draw circles for features points
for (int i = 0; i < features.size(); i++) {
circle(image, features[i], 10, cv::Scalar(250,250,250));
}
for (int y = 0; y < status.size(); y++) {
NSLog(#"Status: %d", status[y]); // always zero
}
std::swap(newFeatures, features);
cv::swap(gray_prev, gray);
}

Answer 1

you should call
cv::goodFeaturesToTrack(gray, features, 20, 0.01, 10);
only for the first initialisation of the features list, and not on every cycle.
What your doing is reseting the features list to match the current frame on every cycle so there is no displacement in the features.
also, if you want just the displacement between two frames you should call
cv::goodFeaturesToTrack(**gray_prev**, features ....

Answer 2

The status gets 0 in two cases:
the feature is outside the image roi
the minimal eigenvalue the gradient matrix of the lucas-kanade window is above the minEigThreshold, i.e. in your window is not enough texture.
However, in my experience the status flags is rather a good guess but not a significant flag to know if the feature has been tracked successfully.
Ignore the status and draw or print your feautures and newFeatures vectors. If they are the same check if gray_prev and gray image are different from each other.