I suggested a db modification in the mailing list that Marcel approved because it was backwards compatible. I think it is suitable for the classifier purpose.
It consists of two new tables: faces and imagefaces.
Faces --> faceid, tagid.
Imagefaces --> imageid, faceid, x1, y1, x2, y2
The faces table is used to match a face with a tag in the database. The other one should be directly written by the classifier. Once you have a trained classifier, it'll first will detect faces in an image. The second step is to assign a different faceid to each different face.
I'd really like to be a part of this, but currently I don't have time.
About the performance of the algorithms, don't be too optimistic. It will be very difficult to recognise ocluded faces. Reducing the number of false positives is easier.
I suggested a db modification in the mailing list that Marcel approved because it was backwards compatible. I think it is suitable for the classifier purpose.
It consists of two new tables: faces and imagefaces.
Faces --> faceid, tagid.
Imagefaces --> imageid, faceid, x1, y1, x2, y2
The faces table is used to match a face with a tag in the database. The other one should be directly written by the classifier. Once you have a trained classifier, it'll first will detect faces in an image. The second step is to assign a different faceid to each different face.
I'd really like to be a part of this, but currently I don't have time.
About the performance of the algorithms, don't be too optimistic. It will be very difficult to recognise ocluded faces. Reducing the number of false positives is easier.