For many pattern recognition methods, high recognition accuracy is obtained at very high expense of computational cost. In this paper, a new algorithm that reduces the computation...
Fang Sun, Shinichiro Omachi, Nei Kato, Hirotomo As...
Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
This paper is focused on algorithmic issues for biometric face verification (i.e., given an image of the face and an identity claim, decide whether they correspond to each other o...
Javier Ortega-Garcia, Joaquin Gonzalez-Rodriguez, ...