Background Subtraction is a technique used in computer vision to separate moving objects from a static background in video sequences. It works by creating a model of the background and then detecting changes in the scene, which are typically caused by moving objects. This method is widely used in applications like surveillance, traffic monitoring, and human-computer interaction. The process involves capturing a series of frames and comparing each new frame to the background model. When significant differences are detected, the moving objects are identified and can be further analyzed. This technique helps in tracking and recognizing objects in real-time scenarios.