A new feature extraction method based on clustering for face recognition

Part 13: Feature Extraction - MinimizationInternational audienceWhen solving a pattern classification problem, it is common to apply a feature extraction method as a pre-processing step, not only to reduce the computation complexity but also to obtain better classification performance by reducing the amount of irrelevant and redundant information in the data. In this study, we investigate a novel schema for linear feature extraction in classification problems. The method we have proposed is based on clustering technique to realize feature extraction. It focuses in identifying and transforming redundant information in the data. A new similarity measure-based trend analysis is devised to identify those features. The simulation results on face recognition show that the proposed method gives better or competitive results when compared to conventional unsupervised methods like PCA and ICA

Born Effective Charges of Barium Titanate: band by band decomposition and sensitivity to structural features

The Born effective charge tensors of Barium Titanate have been calculated for each of its 4 phases. Large effective charges of Ti and O, also predicted by shell model calculations and made plausible by a simplified model, reflect the partial covalent character of the chemical bond. A band by band decomposition confirms that orbital hybridization is not restricted to Ti and O atoms but also involves Ba which appears more covalent than generally assumed. Our calculations reveal a strong dependence of the effective charges on the atomic positions contrasting with a relative insensitivity on isotropic volume changes.Comment: 13 page