1. A system for detecting a feature point of a face, the system comprising: a training unit implemented in a computing apparatus configured to divide each of a plurality of facial images into segments of a predetermined size, and generate an eigen-codebook representing a correlation between a feature vector of each of the divided segments and location of a predetermined feature point in the facial image; and a detection unit implemented in a computing apparatus configured to detect a facial area from a target image, divide the facial area into segments of a predetermined size, detect a feature vector of each of the divided segments of the facial area, and detect a location of a feature point in the facial area by using the detected feature vector and the eigen-codebook, wherein the training unit is configured to obtain M s =[h 1 s ,. .. , h n s ] by applying a predetermined feature point detection algorithm to each segment of the facial image, obtain M E s =[h ave s , h e1 s ,. .. , h eP s s ] by applying Principal Component Analysis (PCA) algorithm to the M s , and generate the eigen-codebook by using the M s and the M E s , wherein h n s is data of a feature vector of a segment s of a n th facial image, M is a matrix, h ave s may be an average among data h 1 s. .. and h n s , h eP s s may represent a piece of eigen data obtained by applying the PCA algorithm to data h 1 s. .. and h n s , and when a piece of eigen data h ei s has an eigen value of λ ei s , λ e1 s >. .. >λ eP s , and P s is a total number of data h e1 s. .. and h eP s s .