I'm currently working on a project where I need to analyze thousands of medium-resolution photos, detect visible faces and blur them out. I've read quite a bit about OpenCV (and spent a day building and playing around with it), and I feel that it's the right direction to solve this problem.
Currently, I have gotten pretty far along with OpenCV, to the point where I can process a photo, pass it to the detectMultiScale() function and use one of the provided Haar cascade files to detect a good number of faces.
However, the hit rate is still pretty abysmal no matter how I play around with the function parameters, or which cascade file I use (frontalface_default vs. frontalface_alt vs. frontalface_alt_tree). I'm perfectly fine with some false positives and false negatives, but I'm nowhere near the rate I'd call acceptable.
:I just copied the details from another question because i have same problem