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—Supervised manifold learning has been successfully applied to action recognition, in which class label information could improve recognition performance. However, the learned manifold may not be able to well preserve both the local structure and global constraint of temporal labels in action sequences. To overcome this problem, this paper proposes a new(More)
This paper proposes a new nonlinear face super resolution algorithm to address an important issue in face recognition from surveillance video namely, recognition of low resolution face image with nonlinear variations. The proposed method learns the nonlinear relationship between low resolution face image and high resolution face image in (nonlinear) kernel(More)
In many practical video surveillance applications, the faces acquired by outdoor cameras are of low resolution and are affected by uncontrolled illumination. Although significant efforts have been made to facilitate face tracking or illumination normalization in unconstrained videos, the approaches developed may not be effective in video surveillance(More)
Face Recognition is used for real time application. So reliability is the more important matter for security. Facial Recognition is rapidly becoming area of interest. Face biometrics is useful for authentication that recognizes face. This paper represents review of face recognition methods and discusses their advantages and disadvantages. The purpose of(More)
In practical face tracking applications, the face region is often small and affected by illumination variations. We address this problem by using a new feature, namely the Gradient-Logarithmic Field (GLF) feature, in the particle filter framework. The GLF feature is robust under illumination variations and the GLF-based tracker does not assume any model for(More)
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