Techniques and Methods Used in Face Recognition

Face recognition is the process of identifying the faces of humans by their unique characteristics. It is a least intrusive technology, as it works with the most authenticating factor, human face. This paper consists of methods and techniques that emphasizes on recognizing a person by comparing the characteristics of his face known or to the already stored images in the database. The techniques and methods discussed in this paper are Principal component Analysis (PCA), Elastic bunch Graph Matching (EGM) algorithm, Linear Discriminant Analysis (LDA), Independent Component Analysis (ICA), Eigen spaces, Knowledge-based, Feature invariant, Template matching, Appearance-based approaches and Microsoft cognitive services. Microsoft Cognitive Services expands on Microsoft's evolving portfolio of machine learning APIs and enables developers to easily add intelligent features – such as emotion and video detection; facial, speech and vision recognition; and speech and language understanding – into their applications.