1. A target detecting method for detecting a target from an input image from a camera, comprising the steps of: a shape detector configured for obtaining camera movement parameters from a movement area in an input image from the camera, and correcting an image frame using the obtained movement parameters, extracting movement candidate areas from the input image frame and a previously input image frame, extracting image feature information from the input image, and extracting a target shape based on the movement candidate areas and the image feature information; a tracker is configured for generating blob information from the extracted shape, and wherein the blob information is an image or an image portion formed by binding adjacent pixels having the same characteristics in the image; extracting blob information for the extracted shape; and checking whether the target is correct by comparing the blob information with that of the shape extracted at the previous frame regardless of background or the camera movement, wherein the extracting image feature information from the input image further comprises skin color areas are extracted from the input image, skin color being extracted as follows: If ⁢ [ C t b ⁡ ( x , y ) > α × C t r ⁡ ( x , y ) ⁢ & ⁢ ⁢ C t b ⁡ ( x , y ) > β × C t r ⁡ ( x , y ) ⁢ & ⁢ ⁢ C t g ⁡ ( x , y ) > γ × C t r ⁡ ( x , y ) ⁢ & ⁢ ⁢ C t g ⁡ ( x , y ) > δ × C t r ⁡ ( x , y ) ] ⁢ & ⁢ [ ⁢ ɛ < ⁢ H [ ⁢ x + w × y ] < η ] ⁢ & ⁢ [ ⁢ ω < ⁢ S [ ⁢ x + w × y ] < ζ ] ⁢ ⁢ Then ⁢ ⁢ f t ⁡ ( x + w × y ) ⁢ ⁢ is ⁢ ⁢ ⁢ skincolor wherein C t r , C t g , and C t b are respectively r, g, and b values of the t-th frame images, H and S are respectively H(ue) and S(aturation) values obtained from C t r , C t g , and C t b , α, β, γ, δ, ε, η, ω, ζ are constants obtained by experiments, and w is a width of the image.