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I am a freshman for face detection. These days I try to compile the OpenCV2.1 code for face detection. I found that there are about 4 cascade files for front face detection, which are "haarcascade_frontalface_alt.xml","haarcascade_frontalface_alt_tree.xml","haarcascade_frontalface_alt2.xml" and "haarcascade_frontalface_default.xml"
I did not find any documents to describe the difference among them, which is prefer for face detection task?
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So what is Haar Cascade? It is an Object Detection Algorithm used to identify faces in an image or a real time video. The algorithm uses edge or line detection features proposed by Viola and Jones in their research paper “Rapid Object Detection using a Boosted Cascade of Simple Features” published in 2001.
Haar Cascade is a machine learning-based approach where a lot of positive and negative images are used to train the classifier. Positive images – These images contain the images which we want our classifier to identify. Negative Images – Images of everything else, which do not contain the object we want to detect.
To get an idea how successful each one is, how many false positives, and how much stuff in total it finds, I ran each XML file on 41,452 magazine covers and made a contact sheet and average of each.
Here are the results on Flickr. The titles show the input XML filename and how many features were detected.
For the files you mention, here's how many features were found:
I didn't count the false positives, you have to check the images for that (for example, the smile file isn't very good, but the faces generally are). Of course, you'll get different results depending on your input data, and magazine covers are generally quite clean photos.
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