Abstract
In this paper, a fully automatic framework is proposed for 3D face recognition and its superiority performance is justified by the FRGC v2 data. For 3D data preprocessing, a new face smoothing method is proposed. Meanwhile, 3D facial representation, which is extracted by the Dual-tree Complex Wavelet Transform (DT-CWT), is introduced to reflect the facial geometry properties. Low redundancy makes it more effective and efficient to describe the discriminant feature in 2.5D range data. In this paper, DT-CWT is used into 2.5D range data in conjunction with the Linear Discriminant Analysis (LDA) to form a rejection classifier, which can quickly eliminate a large number of candidate gallery faces. The remaining faces are then verified using sparse representation based classification. Our method achieves the verification rate of 98.66% on All vs. All experiment at an FAR of 0.1%.