Patent ID: 8811725

Claim:
A learning device, comprising: circuitry configured to: acquire a first plurality of image pairs in which same subjects appear and a second plurality of image pairs in which different subjects appear; set feature points on a first image and a second image of each image pair of the first plurality of image pairs and of the second plurality of image pairs; select a plurality of prescribed feature points set at corresponding same positions on the first image and the second image of each image pair of the first plurality of image pairs and of each image pair of the second plurality of image pairs, so as to thereby select feature extraction filters, which are used to extract a feature for each prescribed feature of the prescribed feature points; extract the feature for each prescribed feature of the prescribed feature points on each of the first image and the second image of each image pair of the first plurality of image pairs and of each image pair of the second plurality of image pairs by using the selected feature extraction filters; calculate a correlation between the extracted features for each image pair of the first plurality of image pairs, and for each image pair of the second plurality of image pairs; and learn same-subject classifiers for identifying whether or not the same subjects appear, on the basis of the calculated correlation and label information representing in which pair of the first plurality of image pairs and of the second plurality of image pairs the same subject appears, wherein the same-subject classifiers comprise at least one strong classifier and at least one weak classifier, and wherein the circuitry is further configured to: learn a same-subject classifier of the same-subject classifiers that is a strong classifier formed of a plurality of weak classifiers, through boosting, and randomly select the prescribed feature points and the feature extraction filters whenever a weak classifier of the plurality of weak classifiers is learned.