Grouping face images using statistic distribution estimate
View Patent ↗A computer-implemented method for sorting face images of different individuals into different groups includes obtaining face images comprising faces of unknown individuals by a computer processor; calculating similarity functions between pairs of face images 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.
1. A computer-implemented method for recognizing face images, comprising:
storing face models or face images of a known person as training faces in a computer storage;
joining a group of testing face images of one or more unknown individuals with a group of training faces that belong to the known person to form a joint face group;
calculating similarity functions, by a computer processor, between pairs of testing face images and training faces in the joint face group;
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 testing face images to belong to the known person if a percentage of the associated similarity functions being true in the joint face group is above a threshold based on the non-negative matrix factorization.
2. The computer-implemented method of claim 1 , further comprising:
merging the testing face images with the training faces of the known person to form a new set of training faces for the known person.
3. The computer-implemented method of claim 1 , wherein the step of conducting non-negative matrix factorization comprises:
forming a non-negative matrix using values of similarity functions between all different pairs of testing face images and training faces in the joint face group,
wherein the non-negative matrix factorization is conducted over the non-negative matrix.
4. The computer-implemented method of claim 1 , wherein the similarity functions in the joint face group are described in a similarity distribution function, wherein the step of conducting non-negative matrix factorization outputs a True similarity distribution function and a False similarity distribution function.
5. The computer-implemented method of claim 4 , wherein the step of identifying the testing face images to belong to the known person comprises:
comparing the similarity distribution function to the True similarity distribution function and the False similarity distribution function.
6. The computer-implemented method of claim 1 , further comprising:
detecting testing faces in images; and
cropping portions of the images to produce the testing face images comprising the testing faces of the one or more unknown individuals.