[Digikam-devel] [Bug 146288] Face detection / recognition for digikam

Alex alexjironkin at gmail.com
Wed Aug 12 21:45:29 BST 2009


https://bugs.kde.org/show_bug.cgi?id=146288





--- Comment #69 from Alex <alexjironkin gmail com>  2009-08-12 22:45:12 ---
http://freshmeat.net/projects/kolmogorov - Seems to have been moved somewhere.

I had an idea. What if we use the classifier that comes with OpenCV as a base,
get the rectangle where the face is. Then use this much smaller image to
identify the face. We can use those small images to train classifier in OpenCV.
In effect current face detect classifier in OpenCV is as general as it can be,
to recognise a generic face, so what we will be creating is a highly specific
classifier tailored for each face in the training data, each face in our
gallery.

Now, what is needed is to improve general OpenCV classifier locally, because
for example, it won't recognise some faces which are altered in spacial domain,
e.g. turned 90 deg left/right. I tested this on my machine with an image of
Lena (popular test image), which it happely recognises in its original form,
but rejects if rotated 90 deg. I had a look at the source code for the
haartraining and it needs to be modified slightly because it creates a fresh
classifier from scratch everytime, where as what we want is one that takes an
existing classifier, then goes through the same motion to update it internally.


Advantages of using OpenCV, as a start, is because it already has lots of
features in its bank. However, if that doesn't work well then we can think of
an alternative way. I hope to get my hands on some image processing books and
papers once I am back at university from holidays. :)

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