I have an application using Haar cascade to detect eyes in the image capture from video camera. The method used is:
void CascadeClassifier::detectMultiScale(const Mat& image, vector<Rect>& objects, double scaleFactor=1.1, int minNeighbors=3, int flags=0, Size minSize=Size(), Size maxSize=Size())
This works quite fine with default value of scaleFactor
, minNeighbors
, and flags
but some people's eyes cannot be detected. So I want to improve the accuracy of eyes detection. It seems like "Cascade Classifier Training" and create the custom cascade classifier is a good solution but before going this way
would it be possible to improve detection accuracy by adjusting some parameters in the method? Please explain more the meaning of scaleFactor
, minNeighbors
, and flags
because those meaning from cascadeclassifier-detectmultiscale docs are not quite clear to me. Thank you.