Automatic image product creation for user accounts comprising large number of images

A computer-implemented method of grouping faces in large user account for creating an image product, comprising:

• selecting, by a computer processor, a first portion of face images from a user's account to add to a first chunk, wherein the first portion of face images is selected to keep chuck size of the first chunk in an optimal chunk size range;
• automatically grouping face images in the first chunk by the computer processor to form face groups, wherein the step of automatically grouping face images in the first chunk comprises:
• calculating similarity functions between pairs of face images in the first chunk by the computer processor;
• joining face images that have values of the similarity functions above a predetermined threshold into a hypothetical face group, wherein the face images in the hypothetical face group hypothetically belong to a same person;
• conducting non-negative matrix factorization on values of the similarity functions in the hypothetical face group to test truthfulness of the hypothetical face group;
• and
• identifying the hypothetical face group as a true face group if a percentage of the associated similarity functions being true is above a threshold based on the non-negative matrix factorization;
• assigning at least some of the face groups in the first chunk to known face models associated with the user account;
• and
• creating a design for an image-based product based at least in part on the face images in the first chunk associated with the face models.

A computer-implemented method of grouping faces in large user account for creating an image product, comprising:

• selecting, by a computer processor, a first portion of face images from a user's account to add to a first chunk, wherein the first portion of face images is selected to keep chuck size of the first chunk in an optimal chunk size range;
• automatically grouping face images in the first chunk by the computer processor to form face groups;
• assigning at least some of the face groups in the first chunk to known face models associated with the user account;
• and
• creating a design for an image-based product based at least in part on the face images in the first chunk associated with the face models, wherein the step of assigning at least some of the face groups in the first chunk to known face models comprises:
• storing training faces associated with the known face models of known persons in a computer storage;
• joining the face images in the first chunk with a group of training faces associated with the known face models;
• calculating similarity functions between pairs of the face images or the training faces in the joint group by a computer processor;
• conducting non-negative matrix factorization on values of the similarity functions in the joint face group to test truthfulness of the joint face group;
• and
• identifying the face images in the first chunk that belong to the known face models if a percentage of the associated similarity functions being true is above a threshold based on the non-negative matrix factorization.