This project uses Python and OpenCV to detect and track objects in videos and from a webcam. It has two modules: one to track objects in uploaded system videos and another to track objects with the webcam. OpenCV algorithms like dense optical flow, sparse optical flow and Kalman filtering are used to track objects by locating them in successive frames. Tracking provides benefits over repeated detection like being faster and able to track objects when detection fails due to occlusion. The project screenshots demonstrate uploading a video and tracking objects within it as well as tracking objects from the webcam stream.