Patent ID: 9317740
Filing Date: 2016-04-19
CPC Classification: G06K,G06T

Claim Text:
1. A method comprising: obtaining a set of training vectors, wherein each training vector is mapped to either a male gender or a female gender, and wherein the training vectors represent facial landmarks derived from respective facial images; identifying, by a computing device, an input vector of facial landmarks, wherein the facial landmarks of the input vector are derived from a particular facial image; selecting, by the computing device, a feature vector containing a subset of the facial landmarks of the input vector, wherein selecting the feature vector comprises: (i) constructing a graph representing the training vectors, each vertex in the graph corresponding to one of the training vectors, (ii) connecting pairs of vertices in the graph using respective uniform weight edges where the corresponding training vectors map to the same gender, (iii) determining a training matrix representing the training vectors, (iv) determining a covariance matrix of the training matrix, (v) using a random forest technique to build a plurality of trees, wherein each node of each tree in the plurality of trees represents a random selection of the facial landmarks, (vi) calculating the Gini importance of the facial landmarks and (vii) selecting the feature vector based on an adjacency matrix of the graph and the Gini importance of the facial landmarks; and based on a weighted comparison between the feature vector and at least some of the training vectors, classifying, by the computing device, the particular facial image as either the male gender or the female gender.