Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
Abstract. Principal Component Analysis (PCA) is one of the most popular techniques for dimensionality reduction of multivariate data points with application areas covering many bra...
A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull...
In principle, the recovery and reconstruction of a 3D object from its 2D view projections require the parameterisation of its shape structure and surface re ectance properties. Exp...
In this paper we propose a domain partitioning RankBoost approach for face recognition. This method uses Local Gabor Binary Pattern Histogram (LGBPH) features for face representat...