Face recognition based on 2D and 3D data fusion

The aim of the work presented in this paper is to present current state of the art of face recognition methods and describe proposal algorithms for face biometric identification that analyse 2D face images and 3D face geometry scans. Data for analysis gathered via 3D scanner are processed through different phases. These are: segmentation phase, feature extraction phase and comparison phase. Segmentation relies on localising characteristic landmark points of the face and projecting the face point cloud onto a plane constructed on the basis of these characteristic points. Feature extraction phase calculates separate feature vectors for 2D and 3D input data. Comparison phase applies fusion of 2D and 3D methods and calculates similarity value between two samples. All samples are compared against one another and results presented as DET curves are generated. By analysis of DET curves, conclusions are formulated.