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Abstract: Face recognition is currently one of the greatest computer vision technologies available. In computer vision, illumination, and other fields, face identification is an extremely challenging task. Posture and expression. Target objects are tracked using face recognition in real- time video images captured with a video camera. It is, in essence, a system program me that can recognize a person from a still photo or video frame. We suggested an automatic face recognition method in this paper. When the person in front of the camera recognizes him, this program me, which is based on face detection, feature extraction, and identification algorithms, automatically detects the human face. We employed the KLT method, the Viola-Jones technique for face detection (which uses a Haar cascade classifier to detect human faces, but the camera constantly detects faces with each frame), and the PCA approach for feature selection. In order to match the geometrical features of the human face, we employ a model-combining technique.