Face Detection is the first step of any face processing system, it finds numerous applications in face recognition, face tracking, facial expression recognition, facial feature extraction, gender classification, clustering, attentive user interfaces, digital cosmetics, biometric systems, digital cameras, video surveillance systems, to name a few. In addition, most of the face detection algorithms can be extended to recognize other objects such as cars, humans, pedestrians, and signs, etc.

Face detection is concerned with finding whether or not there are any faces in a given image (usually in gray scale) and, if present, return the image location and content of each face. This is the first step of any fully automatic system that analyzes the information contained in faces (e.g., identity, gender, expression, age, race and pose).

Basic Face-Detection systems mainly work with upright frontal faces, and several Face-Detection systems have been developed that are able to detect faces fairly accurately with in-plane or out-of-plane rotations in real time.

Face-Detection systems are used in real-time vision modules that interact with humans, particularly in biometrics and human computer interaction as the information contained in faces needs to be analyzed for systems to react accordingly. For biometric systems that use faces as non-intrusive input modules, it is imperative to locate faces in a scene before any recognition algorithm can be applied. An intelligent visionbased user interface should be able to tell the attention focus of the user (i.e., where the user is looking at) in order to respond accordingly. To detect facial features accurately for applications such as digital cosmetics, faces need to be located and registered first to facilitate further processing. It is evident that face detection plays an important and critical role for the success of any face processing systems.