[Digikam-devel] face recognition for digikam

[Gilles Caulier]

Mahesh,

You have post your proposal in digikam ML. Other students working on
this project are also here !!!

Please use google melange interface and post your doc in private. It
will be shared with other mentors

Gilles Caulier

Le 27 mars 2012 22:50, Mahesh Hegde <maheshmhegade at gmail.com> a écrit :
> Project: Face Recognition
>
> Name :Mahesh M Hegde
>
> E-mail :maheshmhegade at gmail.com
>
> Freenode/IRC :mmh
>
> Github:http://goo.gl/Ivblf
>
> Location :Bangalore India
>
> Motivation:
>
> Since Development is continuous process,integrating library like opentld not
> only solves face recognition bug,but also opens many possibilities
> for future development of Digikam,
> for instance i can extend face recognition idea to general object
> recognition.I believe adding feature like face recognition and automatic
> taging which is most requested feature for digikam(492 votes in KDE
> bugzilla),add to user experience a lot.It was long time desire to be
> developer of image editor or part of it.
>
> Proposal Title: Face Recognition, and tagging in digiKam
>
> Implementation:
>
> Digikam already has face detection for most of posture of faces for images
> from album.Also has UI interface for mannual taging with Name string.But
> this information is not being used for recognitionising faces in new
> images.This task needs Face Recognition using modified version of OpenTLD.
>
> OpenTLD is opensource algorithm and working principle is as below:
> As soon as we provide template for tracking object,it initialises intial
> training parameters and confidence parameter.Model consists of growing event
> and proning event,proning event focusses on providing negative examples to
> denoise growing event.Detector and Tracker are key concepts in this
> algorithm since they agree upon position of object of interest.
> I communicated with the author of this algorithm who actually has
> implemented kind of face recognition from a webcam video stream.I discussed
> briefly with regard to our digikam project with him,for sure he will be
> helping us if we face any abstacles.
>
> Face recognition is crucial part of the project which needs to be very
> accurate and precise.Track learn detect is most suitable algorithm for Face
> Recognition.Even though its kind of predator based algorithm,its differs a
> lot from classical approach,it is pretty new algorithm(designed in 2011)
> works very nice with any kind of objects.TLD uses combination of haar
> waveletts and local binary patterns as basis of feature space.Its invariance
> to illumination and still captures sufficient structural information.It has
> confidence parameter which provides possibilities of varying
> accuracy-computation trdeoff.
>
>
> We are not using tracking part of this algorithm as we have already
> implented face detection.OpenTLD implementation is available in cpp.I will
> be modifying and using this library for specific object(Face)
> Recognition.General implementation flow will be storing new Face feature
> vectors in database and comparing and finding minimum distance and percent
> of accuracy with input intensity normalised patch feature vector.
>
> Digikam already has face detection may with very minute bugs i guess,ui
> interface for each detected faces.Tags on regions of image needs coordinates
> defining region,which can be obtained during face detection itself.
>
> PIMO person ontology and NCO contact ontology feature will be added for
> taging,for this purpose i will take help from digiKam team and also from my
> friend who was last year Nepomuk gsocer and developer.
>
> Optionally adding feature to detect birds,animal and commonly used objects.
>
> Tentative Timeline:
>
> 24th April to 10th May:Go through Digikam internal architecture,components
> coordination and source code related to taging so far.
>
> 10th May to 25th May:Work on OpenTLD digikam integration.Library related
> stuff and get rid of mannual selection of image template of
> opentld.Extending one region selection to many region(faces).
>
> 25th June to 10th June:Storing feature space of manually tagged
> templates(faces).And checking and polishing functionality by giving
> "real"stuff,new face detected image.
>
> 10th june to 25 june:Checking for best optional features that can be added
> to improve recognition on cost of computation.
>
> 25th june to 10th july:Finalising feature considerations,integrating with
> Nepomuk may be PIMO person or NCO contact or both of them.
>
> 11th july to 30th july:Removing irrelevent portion opentld source code i.e
> tracking/predator portion of code,achieving stable recognition.
>
> 1st aug to ...:Continue developing Digikam by adding more features like
> testing performance in detecting birds,animals and objects through haar
> classifier which later on can be used for wiki page integration.
>
> About Me:
>
> I am third year telecommunication engineering student of Peoples Education
> Society Institute of Tecnology(PESIT) india.Very passionate about
> image processing.I love playing chess which is one of my hobby.I am
> extremely interested in arteficial neural network.I have developed basic
> image editor in matlab guide framework a year ago,now Source code can be
> found here:http://goo.gl/OERwN  screen shots can be found
> here:http://goo.gl/X7WOr
>
>
> I was advanced track student of machine learning which was offered online
> for free,a few months ago by Andrew NG(stanford lecturer),where i got
> opportunity to programme in octave(matlab equivalent) on interesting systems
> like handwritten number/character recognition,eigen face(principle component
> analysis) recognition,email-spam classification, recommender systems and lot
> more.
>
> I am familiar with KDE,c++ and Qt and matlab/octave.I am good at Linear
> Algebra,algorithms and machine learing.
>
> I am part of  ARKA 2012  2 day event which includes 1 day technical workshop
> on opensource technologies and a 24 hour Hackathon for all opensource
> enthusiasts.I freequently attend FSMK(free software movement karnataka)
> sessions.
>
> expecting suggesions from you