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Pose variance remains a challenging problem for face recognition. In this paper, a scheme including image synthesis and recognition is proposed to improve the performance of automatic face recognition system. In the image synthesis part, a series of pose-variant images are produced based on three images respectively with front, left-profile, right-profile poses, and are added into the gallery in order...
Pose variance remains a challenging problem for face recognition. In this paper, a stereoscopic synthesis method for generating a frontal face image is proposed to improve the performance of automatic face recognition system. Through this method, a frontal face image is generated based on two pose-variant face images. Before the synthesis, face pose estimation, feature point extraction and alignment...
In this paper, a new method of generating optimal face image is proposed for improving the performance of automatic face recognition system. In order to overcome the influences of variations in face pose and expression, it is essential to generate optimal face image for the face to be recognized. The optimal face image is the one which has the minimum pose rotation and neutral expression in image...
In this paper, we present face pose estimate and multi-pose synthesis technique. Through combining composite principal component analysis (CPCA) of the shape feature and context feature respectively in eigenspace, we can get new eigenvectors to represent the human face pose. Support vector machine (SVM) has the optimal hyperplane that the expected classification error for unseen test samples is minimized...
In this paper, a new theory of optimal-face generating is proposed to improve recognition rate of face image. Its aim is to solve how to select a relatively better face image to be recognized in dynamic face recognition system. The proposed theory improves the system performance by integrating the effects of multiple factors including pose, illuminating, expression and resolution. A new system is...
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