[Digikam-devel] Re: Face detection

Aditya Bhatt adityabhatt1991 at gmail.com
Fri Nov 5 16:07:50 CET 2010

On Fri, Nov 5, 2010 at 7:55 PM, Marcel Wiesweg <marcel.wiesweg at gmx.de>wrote:

> > I think it really is the first tag I added.
> >
> > And those faces confused are already quite well trained, i.e. > 50
> pitures
> > confirmed for each.
> I'll test face recognition. Maybe it simply still doesnt work.
I recall that there was a bug in libface, the very first training has to be
done with more than one tag IDs. That is, in the very first training of the
database, all the faces in the training vector should not have the same ID.
This is an issue with the very nature of the algorithm.
Two ways to fix this :
*Patching libface*
I might take a look into how to fix this soon, most likely it will be fixed
by appending a dummy face with a special ID (one that will be never assigned
by digikam normally).

*Workaround in digiKam*
I haven't looked in the new code about how things are done, but the faces
could be given for training in bunches of 10 or 20 at a time.

The second way is rather hackish however, and I'd look at patching libface
as a solution to this.

> > This gets me to another point. Would it be possible to not only have
> > unknown pictures but groups of unknown, i.e. digikam should be able to
> > guess which faces might look the same although it does not know their
> > name.
> I have already thought of this. No idea if face recognition technology
> availalbe to us is ready for this.
About grouping within the "Unknown" set:
This, although possible in theory, is *very* computationally expensive. It
requires a clustering algorithm to condense the faces into groups, however,
in the clustering, the computation of the "distance" between faces in the
face space is computationally. More so because the dimension of the face
space changes with the amount of faces, plus the number of unknown faces is
supposed to change so frequently that a re-clustering every now and then
would be required. AFAIK, none of the 'competition' do this.

> > And also, what happens if a user scans the whole collection and ends up
> > with thousands of pictures in unknown? He would have to assign tags to
> > each of them and digikam would not try automatically to guess faces again
> > after it got some training. So the user would have to know about the
> > "recognise again" feature in the scanning GUI. I think there should be
> > some smartness in digikam that at least asks after x pictures training
> for
> > a tag whether it should try to find all pictures for that person.
> Yes, interesting idea.

I support this idea too.

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