1. A learning method for causing a face classification apparatus to learn a characteristic feature of faces, wherein the face classification apparatus is an apparatus for classifying whether an input image is a facial image including a face which has a predetermined direction and a predetermined angle of inclination, wherein the characteristic feature of faces is learned by using a machine-learning method using a plurality of facial images for learning, which are different from each other, and each of which includes a face which has the predetermined direction and the predetermined angle of inclination, said learning method comprising the steps of: setting initial value of weight for each of all sample images to 1, said sample images includes said facial images for learning and plural images which are recognized as non-facial images; creating plural weak classifiers; selecting the most effective weak classifier from said plural weak classifiers; comparing correct answer rate of the selected weak classifier and a predetermined threshold value; determining type and classification condition of weak classifier used for classification, if the correct answer rate of the selected weak classifier has exceeded the predetermined threshold value; and excluding said selected weak classifier, increasing weight of sample image which has not been correctly classified and reducing weight of sample image which has been correctly classified, if the corrected answer rate of the selected weak classifier has not exceeded the predetermined threshold value; wherein, in the step of creating plural weak classifiers, a weak classifier is created for each of a plurality of types of set of pairs, said each of the plurality of types of sets of pairs includes predetermined two points, which are set in the plane of the sample image of reduced images of the sample image, wherein each of said weak classifiers provides a criterion for classifying images into facial images or non-facial images by using a combination of difference values in luminance between two points in each of pairs which form a single set of pairs, said single set of pairs includes a plurality of pairs and said plurality of pairs includes predetermined two points set in a plane of the partial image extracted by using a sub-window or in a plane of each of reduced images of the partial image, and wherein the plurality of facial images for learning includes only images of a predetermined facial region and is determined so that characteristic features included in said plurality of facial images for learning are not different from each other.