Pose Invariant Face Recognition Based on 3D Model

An estimating pose angle method based on fuzzy math and a layered face recognition method by matching 2D probe image to 3D model were proposed in this paper. After classifying multi-pose images to different pose space, Primary Component Analysis (PCA) was used to get eigenfaces in the given pose space. While a probe image was recognized, its pose and fuzzy angle were estimated firstly and then they were matched in the estimated pose space by PCA method. Some candidates were gotten by upwards step and their 3D model were employed to generate dynamically virtual 2D images with view angles nearby fuzzy angle. Image correlation was employed as a classifier to match the probe image to the virtual images. The experiment result shows that the proposed method is robust to pose variant.