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Two schemes are proposed for face recognition.
Numerous studies [1] have been greatly proposed for face recognition recently.
Conventionally, learning-based SR methods using principal component analysis (PCA) have been proposed for face hallucination [19].
In this context, an evolutionary single Gabor kernel (ESGK) based filter approach is proposed for face recognition.
In this paper a multi-classifier system based on color and texture information is proposed for face image segmentation.
In the first category, the object detection method of Viola and Jones [4], originally proposed for face detection, is a popular approach to locating landmarks [5 7].
Similar(50)
An active tooth surface design methodology is proposed for face-hobbed hypoid gears based on fitting the measuring coordinates of real tooth surface that includes the flank deviations caused by machine errors and the deformation of heat treatment.
A computationally efficient load distribution model is proposed for both face-milled and face-hobbed hypoid gears produced by Formate and generate processes.
A novel resolution invariant local feature based method is proposed for 3D face recognition.
For instance, in [12] a sparse representation-based classification (SRC) method was proposed for robust face recognition and achieved very impressive results.
In fact, the same problem exists in face recognition and several methods proposed for pose-invariant face recognition [8 11] can be applied to the lipreading problem.
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