The present invention relates to the field of computer vision, and relates in particular to a facial key point marking method. The facial key point marking method comprises two processes, respectively a training process and a using process, the training process and the using process both comprising rigid body evolution and non-rigid body evolution, the rigid body evolution and the non-rigid body evolution being capable of performing multiple iterations. The method comprises: step S1: eliminating an affine conversion difference between an initial template and real coordinates via the rigid body evolution of the training process; step S2: performing individual adjustment on each facial key point within the initial template via the non-rigid body evolution of the training process, so as to increase the positioning accuracy of the facial key points; step S3: via the rigid body evolution of the using process, performing facial key point prediction according to a linear regression model, and calculating new positions of the facial key points; step S4: in the non-rigid body evolution of the using process, adjusting the coordinates of the facial key points according to the new positions, and obtaining a prediction result.
FACIAL KEY POINT MARKING METHOD