Design and Analysis of Statistical Methods on Face Recognition in Bloomington, MN

Face is an important biometric feature for personal identification. Human beings easily detect and identify faces in a scene but it is very challenging for an automated system to achieve such objectives. Dimensionality reduction has been a key problem in Face Recognition. Independent Component Analysis (ICA) is a recent approach for dimensionality reduction. Locality Preserving Projections (LPP) and linear collaborative discriminant regression methods are also a recently proposed new methods in pattern recognition for feature extraction and dimension reduction.