The goal of this work is to develop a system to track and classify objects as they move across a confined field of view and accomplish this at a real time frame rate. By using a stationary camera and by using the experimental fact that image pixel values show a normal distribution I can attain a robust separation of foreground objects from background objects using only a mean and standard deviation. This simple separation allows for a more robust tracking mechanism. The tracking mechanism searches the image based on prior knowledge of the scene and a set of event probabilities that serve to simplify the searching and data collection.