This paper proposes a pose estimation and frontal face detection algorithm for face recognition. Considering it's application in a real-world environment, the algorithm has to be robust yet computationally efficient. The main contribution of this paper is the efficient face localization, scale and pose estimation using color models. Simulation results showed very low computational load when compare to other face detection algorithm. The second contribution is the introduction of low dimensional statistical face geometrical model. Compared to other statistical face model the proposed method models the face geometry efficiently. The algorithm is demonstrated on a real-time system. The simulation results indicate that the proposed algorithm is computationally efficient.
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