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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