Tracking

Tracking in computer vision AI refers to the process of identifying and following objects or people in a video stream. The objective of tracking is to understand the movement patterns of these objects or people and provide information about their location, speed, and direction of movement. This information can be used in various applications, such as surveillance, autonomous vehicles, and robotics.

Tracking in computer vision AI involves several techniques, including object detection, motion estimation, and data association. Object detection is used to identify objects of interest in the video stream, while motion estimation is used to determine the movement of these objects over time. Data association is used to match the objects detected in one frame of the video with those detected in the previous frame. By combining these techniques, tracking algorithms can provide accurate and reliable information about the movement of objects or people in a video stream, making them an essential tool in computer vision AI.