A Neuro-fuzzy Approach to User Attention Recognition
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Multimedia Tools and Applications
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In this paper, we propose a new approach for face pose estimation based on two images from different views under certain conditions. Using a weak-perspective imaging model, six pose parameters were deduced, with four pairs of feature points properly chosen across the two face images. Through the scan-iteration algorithm, a robust performance was achieved, without solving non-linear equations. Comparing to some other methods which estimate rotation matrix based on fundamental matrix (F), our method focuses on the "absolute pose" with respect to front view rather than the "relative pose" between the two face images. "Absolute pose" is indispensable in most situations especially for 3D face modeling. Since our method does not depend on any 3-D face models and frontal-view images, it can be applied not only to face recognition and 3-D face modeling, but also to other relevant applications. Experimental results demonstrate the efficiency of our method.