https://bugs.kde.org/show_bug.cgi?id=437896
Thilo <[email protected]> changed: What |Removed |Added ---------------------------------------------------------------------------- CC| |[email protected] --- Comment #1 from Thilo <[email protected]> --- Hi Martin, (In reply to Martin from comment #0) > First of all, it is a great software you have programmed. Thank you! > > I have a lot of Photos in my database spanning a large period of time. And > as we are all no Hollywood stars, our look changes with time. > Would it be possible to cluster the Face-Recognition Data with time ? > > e.g. If a large time period is specified, take 10y for a face. If it's not > the first years of life, this should improve Recognition a lot. Otherwise I > would have to use different "Persons" in the database e.g. Gandalf 1..2y, > Gandalf 3..5y Gandalf 6..12, and so on. > > Also I would really like to see "second best match". When I do not confirm a > face from a suggestion, I would like that to be calculated to match another > face WITHOUT the one I disconfirmed. Would that be possible ? > > Thank you. Hi Martin! I also thought of this problem of growing children, there is some research on this (A Review of Face Recognition against Longitudinal Child Faces; Sodomsky) and I like your proposition. Since most parents really take a lot of pictures, data should be sufficient to train "yearly" models of childrens persons. I do not know, if digikam is able to internally maintain a 1:n relationship between person labels and face recognition models, but I think this would be a senseful improvement. An alternative would be to have a hiearchy where you have a personlabel and "under" it some person-age labels. there is a recognition model for person-age which is individually trained and when it is recognized the face is automatically labeled person and person-age. However, the recognition experts here can maybe raise their opinion if change like the proposed would improve the recognition performance for children -- You are receiving this mail because: You are watching all bug changes.
