fully automatic system that analyzes the information contained in faces (e.g., identity, gender, expression, age, race, and pose). The current evolution in computer technology in recent years has facilitated the development of real-time computer human interaction. Examples can be found, particularly in biometrics and human computer interaction, as the information contained in faces needs to be analyzed for systems to react accordingly (Yang, 2009). Faces first need to be located and registered to
Abstract—Facial Expression Recognition refers to the classification of facial features in one of the basic emotions: happiness, sadness, fear, disgust, surprise, anger and neutral. It is performed by means of feature extraction. Principle Component Analysis is a technique among the most common feature extraction technique used in Facial Expression Recognition. In this paper, a Facial Expression Recognition System for human’s expression identification using Principle Component Analysis with City-Block
recognition system. It is also used in video surveillance and human electronic computer interface. Some novel digital cameras custom face detection for auto focus. Face detection is an electronic computer technology that limits the locations and sizes of earthborn face in arbitrary conception. It detects only facial features and ignores the background. Face detection is a novel approach through which we can extract the facial features from a human body. [11] Face recognition system categorizes into two