Real Time Mean Shift Tracking using Optical Flow Distribution

This paper describes about real-time object tracking method based on mean shift tracking algorithm. The mean shift tracking algorithm is an efficient technique for tracking object through an image. The original mean shift tracking is proposed to apply the color image based on the color distribution. A near-infrared camera is used with surveillance system to take in the dark. It is difficult to track the target object in the low contrast image such as the infrared image. To overcome this problem, our idea is to consider optical flow distribution. The proposed method is integrated three distributions (color, flow magnitude and flow direction). Experiments were conducted for the color image and the infrared image compared with the original method. It is shown that our method is able to track a target object in the low contrast image