|Project Description: ||With the advancement of computer power availiable on most home computers, interacting with the computer by visual means is becoming possible and probable. Computer vision provides the ability for facial recognition and other biometrics, emotion sensing, robotics, and many other forms of autonomous interaction. All of these tasks require that the computer be able to locate and track the human face, through a visual sensor, like a camera. Through the use of Haar cascade classifiers for detection and the Lucas-Kanade algorithm, the CAMSHAFT algorithm, and active contours for feature tracking, this project created an application that can detect and track the human face, mouth, nose, and eyes when they are present in a camera video stream. By using the Open Cumputer Vision(OpenCV) library, this program can easily be ported to a new platform.