An introduction to face-recognition methods and its implementation in software applications

Face detection and recognition technology has shown a steep development in the field of scientific research and is subsequently harvesting growing interest from the industry, which in fact can be confirmed seeing numerous implementations in forms of commercial applications such as autofocus in digital cameras, human computer interfaces in smartphones, or even video surveillance cameras in airports. In response to this growing interest and willingness to implement this technology of face detection and face recognition technology, this paper will provide the readers with fundamental knowledge of how face detection essentially works and ought to help the readers to establish a foothold in developing own ideas using face detection technology. The main purpose of this research paper is to introduce several significant principles of current face-detecting methods such as active shape model (ASM), active appearance model (AAM) and constrained local models (CLM) in a comprehensive manner and to provide some insight on closely related topics such as principal component analysis and eigenfaces. In this paper, we will also present selected examples of implementations of above mentioned face-detecting methods via open-source software applications such as of xFacetracker and FaceSubstitution with openFrameworks.