Image-based Face Detection and Recognition: "State of the Art"
It addresses the problem of improving accuracy and speed in face recognition for security surveillance, but it is incremental as it builds on existing methods.
This paper evaluates various face detection and recognition methods to provide a complete solution with higher accuracy and better response rate for image-based systems, as an initial step for video surveillance.
Face recognition from image or video is a popular topic in biometrics research. Many public places usually have surveillance cameras for video capture and these cameras have their significant value for security purpose. It is widely acknowledged that the face recognition have played an important role in surveillance system as it doesn't need the object's cooperation. The actual advantages of face based identification over other biometrics are uniqueness and acceptance. As human face is a dynamic object having high degree of variability in its appearance, that makes face detection a difficult problem in computer vision. In this field, accuracy and speed of identification is a main issue. The goal of this paper is to evaluate various face detection and recognition methods, provide complete solution for image based face detection and recognition with higher accuracy, better response rate as an initial step for video surveillance. Solution is proposed based on performed tests on various face rich databases in terms of subjects, pose, emotions, race and light.