Published Paper Details:

Face detection is a computer technique that determines the positions and sizes of human faces in arbitrary video and images. It detects countenance and ignores anything like buildings, trees and bodies. Human vision awareness is currently a lively research area within the computer vision community. Human facial localization and identification is usually the primary step in applications like video monitoring, human computer interface, face recognition and image management. Identifying and tracking human faces may be a necessity for face recognition and / or countenance analysis, although there's often a generalized face image available. the matter of computer-based face recognition using unbiased facial data as an analysis remains a largely unexplained area of research. Given how humans perceive faces and the way they differ from verification machines, it should be fascinating to ascertain how machines favor different countenance, instead of presenting face recognition difficulties. . Therefore, this paper examines the question, which involves the thought of face recognition using incomplete facial information. The experiment is predicated on the utilization of Object Oriented programing language (OOP) with OPENCV (Open Computer Vision) for correct classification and identification of the face. During this paper we shall implement a Har-Classifier for Face Detection and Tracking supported the Har features.