[digiKam-users] face recognition
frederic.chaume at gmail.com
Mon Nov 12 18:34:01 GMT 2018
thanks a lot for this clarification.
IA in DK ! I look forward to see more on this! if he can do all this
for us , but I beleive that's the purpose :-)
did you look also to my second point:
also a problem I have (not new in DK6), after a search, when I'm looking
to the unconfirmed, I see different proposals, and when the proposal is
incorrect, if I enter the correct name, then it seems to become the
standart proposal for most of the remaining unconfirmed.
is there something I'm doing wrong ?
I have also another error: the tag "unconfirmed" is no more visible (I
have removed it) , but not able to re-create it as it still exist. How
to make it visible again?
Le 12/11/2018 à 07:37, Gilles Caulier a écrit :
> Le dim. 11 nov. 2018 à 11:22, frederic chaume
> <frederic.chaume at gmail.com <mailto:frederic.chaume at gmail.com>> a écrit :
> Hi all
> trying to experiment the face recognition from DK6B2, and I see now
> there are 4 different algorithms. What are the differences ?
> This is 4 different algorithms to process face fingerprints while
> faces recognition.
> This is not the face detection processing, which is another one.
> Detection is one step, recognition is another one.
> The 3 first one recognition algorithm are standard method more and
> less efficient to process recognition :
> LPB : the original method and the first one implemented in DK.
> EigenFace : This algorithm was never finalized in DK when FR have been
> implemented in DK. It's not finalized and given for testing and
> compare with LPB
> FisherFace : This algorithm is an improvement of EigenFace. It's not
> fully implemented and given to compare with LPB (it do not store data
> in database has i remember).
> LPB, EighenFace, and Fisherface use OpenCV library implementation as
> well. So the performance are relevant of OpenCV code. In DK, we have a
> template implementation of recognition engine which can be extended
> through virtual methods, as plenty of algorithm variant exists to
> perform face recognition.
> Between LPB, EigenFace and FisherFace, LPB is the most faster. The
> recognition efficience is mostly the same (good recognition vs false
> Eigen and Fisher run more slowly than LPB.
> These algorithms need at least 6 faces already tagged by end users
> with the same person to recognize to start to give suitable results,
> but if more reference are given, it must be better. Typically you
> provide samples to use to process future comparison using face
> histogram stored in database. You can only provide real face sample to
> compare. You cannot teach about false positive results. The teach
> process still basic.
> The last one is more tedious and promising but it's so far not
> optimized. It's an IA algorithm using deep learning based on DLib. You
> teach face to the neural network and it store data in database. The
> result are good if you teach many faces to the IA. The result are
> good, but the speed no. It's slow and require more end user action to
> work. So this one need a lots of improvement for the future and cannot
> be used as well actually. This IA can teach for false positive
> detected as flower seen as a face for ex. So the teach process is more
> complete, but require more data storage in database.
> IA and deep learning are the future and look promising. It's also a
> very interesting project to implement (from a student viewpoint), as
> IA start to be used everywhere in computer science. So i'm sure that
> we will found new students to work on it later, as it still a lots of
> work to do on it.
> So the only one to use for the moment is LPB.
> Gilles Caulier
> also a problem I have (not new in DK6), after asearch, when I'm
> to the unconfirmed, I see different proposals, and when the
> proposal is
> incorrect, if I enter the correct name, then it seems to become the
> standart proposal for most of the remaining unconfirmed.
> is there something I'm doing wrong ?
> thanks for your help
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