Face Analysis, Modeling and Recognition Systems

Face recognition is a type of biometric software application that can identify a specific individual in a digital image by analysing and comparing patterns. A facial recognition system is a computer application capable of identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. Facial recognition systems are commonly used for security purposes but are increasingly being used in a variety of other applications. In addition to being used for security systems, establishments have found a number of other applications for facial recognition systems. Some facial recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face. For instance, an algorithm may analyse the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features are then used to search for other images with matching features. Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face recognition. A probe image is then compared with the face data. One of the earliest successful systems is based on template matching techniques applied to a set of salient facial features, providing a sort of compressed face representation. The book named Face Analysis, Modeling and Recognition Systems offers a concise and inclusive analysis of artificial face recognition domain through major areas of interest: biometrics, robotics, image databases and cognitive models. The topics in this book describe numerous novel face analysis techniques and approach many unsolved issues. It will be of special interest to academics and researchers interested in computer vision, biometrics, image processing, pattern recognition and medical diagnosis.