Subspace State Estimator for Facial Biometric Verification

摘要

This paper proposes a new Subspace State Estimator (SSE) algorithm for facial biometric verification. In the proposed method, a sequential estimator is being designed in the image subspace which addresses the challenges due to nonlinear, no stationary, and heterogeneous noise. The proposed model includes a subspace method that overcomes the computational complexity associated with the sequential estimator. The theoretical foundation of the proposed method along with the experimental results are also presented in this paper. For the experimental evaluation of the proposed method, facial images from the public "Put Face Database" have been used. The experimental results demonstrate the superiority of the proposed method in comparison with its counterparts.