1. A method of detecting a position of a face feature point by using an Adaboost learning algorithm, the method comprising: (a) classifying a sub-window image into a first feature point candidate recommendation image and a first feature point candidate non-recommendation image by using first feature patterns selected through the Adaboost learning algorithm, and generating first feature point candidate position information of the first feature point candidate recommendation image; and (b) re-classifying the sub-window image classified as the first feature point candidate non-recommendation image into a second feature point candidate recommendation image and a second feature point candidate non-recommendation image by using second feature patterns selected through the Adaboost learning algorithm, and generating second feature point candidate position information of the second feature point candidate recommendation image; (c) storing the first feature point candidate position information and pieces of the second feature point candidate position information for sub-window images of a facial image; and (d) forming clusters by performing clustering in view of the first feature point candidate position information and the second feature point candidate position information, and generating position information of a certain representative position of the first feature point candidate position information and the second feature point candidate position information forming a largest cluster among the clusters as feature point position information.