Face Recognition has benefitted greatly from the many databases that have been produced to study it. Most of these databases have been created under controlled conditions to facilitate the study of specific parameters on the Face Recognition problem. These parameters include such variables as Position, Pose, Lighting, Expression, Background, Camera Quality, Occlusion, Age, and Gender. While there are many applications for Face Recognition Technology in which one can control the parameters of Image Acquisition, there are also many applications in which the practitioner has little or no control over such parameters. This paper is provided as an aid in studying the latter, unconstrained, face recognition problem. The database represents an initial attempt to provide a set of labeled face photographs spanning the range of conditions typically encountered by people in their everyday lives. This paper describes a face detection system which goes beyond traditional face detection approaches normally designed for single faced images. The system described in this paper has been designed taking into account spatial coherence contained in multiple face detection. The resulting system builds a feature based model for each detected face, and searches them using various model information in the database. It provides a feasible way to locate the positions of two eyeballs, near and far corners of eyes, midpoint of nostrils and mouth corners from face image. This approach would help to extract useful features on human face automatically and improve the accuracy of face recognition.