Detecting facial similarity based on human perception of facial similarity

A computer-useable medium, which is not a signal, storing a computer program, the computer program including instructions for causing a computer to perform the following operations:

• determine inequalities between training faces, where the inequalities represent perceptions of one or more training users regarding a similarity of a first set of two, different training faces relative to a similarity of a second set of two, different training faces;
• determine training feature vectors in an objective feature space based on the training faces, wherein the training feature vectors are separated by objective differences;
• optimize a function over a matrix M that maximizes a correlation between the training feature vectors in the objective feature space and the inequalities;
• determine a mapping function between the objective feature space and a psychological feature space based on the matrix M;
• determine, based on the determined mapping function, similarity information that indicates human perception of facial similarity;
• receive a query image that includes a query face;
• determine one or more search result images that include at least one face that is similar to the query face based on the similarity information that indicates the human perception of facial similarity;
• and
• provide the search result images to a user.

A system comprising:

• means for determining, by one or more processors, inequalities between training faces, where the inequalities represent perceptions of one or more training users regarding a similarity of a first set of two, different training faces relative to a similarity of a second set of two, different training faces;
• means for determining, by the one or more processors, training feature vectors in an objective feature space based on the training faces, wherein the training feature vectors are separated by objective differences;
• means for optimizing, by the one or more processors, a function over a matrix M that maximizes a correlation between the training feature vectors in the objective feature space and the inequalities;
• means for determining, by the one or more processors, a mapping function between the objective feature space and a psychological feature space based on the matrix M;
• means for determining, by the one or more processors and based on the determined mapping function, similarity information that indicates human perception of facial similarity;
• means for receiving, by the one or more processors, a query image that includes a query face;
• means for determining, by the one or more processors, one or more search result images that include at least one face that is similar to the query face based on the similarity information that indicates the human perception of facial similarity;
• and
• means for providing, by the one or more processors, the search result images to a user.

A method for determining similar faces within images based on a user's perception of facial similarity, the method comprising:

• accessing, by one or more processors, training data, where the training data represent perceptions of one or more training users regarding a similarity of a first set of two, different training faces relative to a similarity of a second set of two, different training faces;
• determining, by the one or more processors, training feature vectors in an objective feature space based on the training faces, wherein the training feature vectors are separated by objective differences;
• minimizing, by the one or more processors, a function that (1) correlates distances between (i) the training feature vectors in the objective feature space and (ii) the training feature vectors mapped into a psychological feature space using a matrix M and (2) evaluates whether inequalities between the feature vectors mapped into the psychological feature space using the matrix M match inequalities that represent the perceptions of the one or more training users;
• determining, by the one or more processors and based on the accessed training data and the matrix M, similarity information that indicates human perception of facial similarity;
• receiving, by the one or more processors, a query image that includes a query face;
• determining, by the one or more processors, one or more search result images that include at least one face that is similar to the query face based on the similarity information that indicates the human perception of facial similarity;
• and
• providing, by the one or more processors, the search result images to a user,
• wherein the matrix M includes an array of multipliers that correspond to elements of the training feature vectors.