Academy & Industry Research Collaboration Center
Face is one of the most important biometric traits for its uniqueness and robustness. For these reason researchers from many diversified fields, like: security, psychology, image processing, and computer vision, started to do research on face detection as well as facial expression recognition. Subspace learning methods work very good for recognizing same facial features. Among subspace learning techniques PCA, ICA, NMF are the most prominent topics. In this paper, the authors' main focus is on Independent Component Analysis (ICA). Among several architectures of ICA, they used here FastICA and LS-ICA algorithm.