The Shi-Tomasi Corner Detector in python OpenCV looks like this:
feature_params = dict(maxCorners=100, qualityLevel=0.3, minDistance=7, blockSize=7)
p0 = cv2.goodFeaturesToTrack(frame, mask=None, **feature_params)
The documentation says that the parameter qualityLevel is the minimal accepted quality of image corners. It also says that this parameter value is multiplied by the best corner quality measure, and the corners with the quality measure less than the product are rejected.
For example, if the best corner has the quality measure = 1500, and the qualityLevel=0.01 , then all the corners with the quality measure less than 15 are rejected.
If I want to set the quality measure instead of the quality level, how can I do it?
The quality level is not an absolute parameter. By that, I mean that the quality level depends on the best corner quality measure, which at the same time depends on the background. However, if I can set this quality measure, I will be able to supress those dependencies.
