Estimation of eyeglassless facial images using principal component analysis

For facial image analysis, facial parts such as eyes, nose, and mouth are generally focused and used. When these facial parts are hindered by additional objects (eyeglasses, beard, injury, etc.), the feature extraction from facial image will not be accurate. In this paper, we focus on the eyeglass faces because they account for 40% of population in Japan, and present a method of the removal of eyeglass frame in facial images with eyeglasses using principal component analysts. Two approaches are discussed for removal of eyeglasses in facial image. The first method calculates basis vectors from many eyeglassless facial images and one eyeglass facial image, and reconstructs the facial image with the basis vectors which include no feature of eyeglass frame. The second method calculates basis vectors from a set of eyeglassless facial images, and reconstructs the facial image using the values of inner product of the basis vectors and an eyeglass facial image. The former obtains the images which restrain. The features of eyeglass frame while loses the facial individuality a little. The latter obtains a natural eyeglassless facial image