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A new unsupervised filter-based feature selection method is introduced. Its principle consists in merging similar features into clusters using a distance measure derived from the correlation coefficient. Subsequently, only one representative feature is selected from each cluster. In experiments with real-world data, we show that the proposed method is benefical as a pre-filtering step for more sophisticated...
We describe a personal identity verification system based on lip dynamics biometric. The lip shape is represented in terms of a B-spline model, tracked over time. The coordinates of the 11 control points of the B-spline model are used as features for each frame. An utterance consisting of N frames produces a sequence of 22 dimensional feature vectors that is matched to the template using dynamic time...
We address the problem of pose-invariant face recognition based on a single model image. To cope with novel view face images, a model of the effect of pose changes on face appearance must be available. Face images at an arbitrary pose can be mapped to a reference pose by the model yielding view-invariant representation. Such a model typically relies on dense correspondences of different view face...
We present a comparison of several face representation methods from the point of view of their sensitivity to illumination changes. The sensitivity is measured in terms of the overlap of the distributions of normalized correlations used for inter class and intra class image comparisons. The result suggests, that better illumination invariance could be achieved in feature spaces in the frequency domain...
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