1. A method for generating an object classifier for at least one image region, wherein each image region in the at least one image region includes at least one two-cell structures, and each two-cell structure is composed of a center cell and a neighbor cell which is one of eight cells around and adjacent to the center cell, the method comprising: feature space calculating step for calculating a feature space by applying a descriptor generation method for generating a two-cell structure feature descriptor for each of the at least one two-cell structure included in each of the at least one image region; and generating step for generating the object classifier based on the determined feature space, wherein the descriptor generation method comprises: calculating step for calculating statistics of gradients in the center cell and the neighbor cell respectively; and comparing step for comparing the calculated statistics of gradients in the center cell and the neighbor cell, so as to obtain a two-cell structure feature descriptor for describing the feature of the two-cell structure, wherein the two-cell structure feature descriptor is one bit binary value, and the generating step further comprises: determining step for determining each of at least one specific-cell structure feature for the at least one image region based on the calculated feature space using a heuristic algorithm, wherein the specific-cell structure feature is a N-bit binary value, N corresponding to the number of two-cell structure feature descriptors constituting the specific-cell structure feature and the value of each bit in the N-bit binary value corresponding to one of N two-cell structure feature descriptors o included in the specific cell structure; wherein the object classifier is generated from at least one specific-cell structure feature; and wherein N is larger than or equal to 1.