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Face Detection and Recognition Using Ada Boost-ICA Algorithm


K Somashekar, Puttamadappa C


Vol. 13  No. 12  pp. 132-136


Face recognition mainly involves recognizing personal identity, based on statistical as well as geometrical features which are derived from face images .This paper presents an automated system for human face recognition in a real time background world for a large homemade dataset of persons face. The task is very difficult as the real time background subtraction in an image is still a challenge. Addition to this there is a huge variation in human face image in terms of size, pose and expression. To detect real time human face AdaBoost algorithm is used and a simple fastICA is used to recognize the faces detected. Our method basically consists of two main parts: firstly we detect faces and then recognize the detected faces. Even every one can detect and identify faces in respective data with little or no effort, but building an automated system that will accomplishes such objectives is, however, very challenging. These challenges are even more profound when one considers the large variations in the visual stimulus due to illumination conditions, directions of viewing or poses, facial expression or changes, aging, and disguises such as facial hair, as well as glasses also. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the Face recognition research provides the cutting edge technologies in commercial, law enforcement, and military applications. So that an automated vision system that willperforms the functions of face detection, verification and as well asrecognition willfind countless unobtrusive applications, such as airport security and access control, building (embassy) surveillance and monitoring,human-computer intelligent interaction and perceptualinterfaces, and smart environments at home, office, and cars.


ADA, Face Detection, ICA, Recognition,PCA