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.