Tracking-Learning-Detection

Tracking-Learning-Detection (TLD) is a computer vision method that enables a system to follow an object in a video, understand its features, and detect it even if it temporarily leaves the frame. Initially, it follows the object based on its current appearance (tracking), then updates its understanding of the object's features to adapt to changes (learning), and finally searches for the object in new frames using this knowledge (detection). This continuous cycle allows the system to robustly track objects over time, even when conditions change or the object partially disappears and reappears.