The invention is applied to the technical field of human face identification, and provides a human face identifying method and a human face identifying device; the method comprises the following steps: extracting high-dimensional characteristics of a training sample and a to-be-identified human face image pair, and carrying out segmentation and dimensionality reduction on the high-dimensional characteristics; defining a latent factor model, wherein the latent factor analysis model expresses the characteristics as a linear combination of an identity factor, an age factor, a mean value and a noise; inputting the characteristics of the training sample, and optimizing the latent factor model via maximum likelihood estimation, wherein an objective function is a latent factor joint probability in a logarithmic form; inputting the characteristics of the human face image pair to the trained latent factor model and calculating a likelihood ratio, wherein the likelihood ratio is the ratio of the first probability to the second probability; and expressing a similarity with the likelihood ratio, and if the similarity is higher than a preset threshold value, identifying the human face image pair as the same person. According to the method and the device disclosed by the invention, the accuracy rate of the human face identification is improved.