Research on improved tracking algorithm for complex environmental problems

In order to solve the complex environmental problems faced by the drone tracking target, the MeanShift algorithm based on color feature tracking is selected and improved. Aiming at the problem that the target color is similar to the environment background when the target is tracked by the drone, the tracking feature of the MeanShift algorithm is proposed. The video format captured by the camera is converted from the RGB color space to the HSV color space, and the hue component is selected as the tracking feature. For the problem that the target is short-term occlusion during the tracking process of the UAV, the improved MeanShift algorithm is combined with Kalman filtering, and the prediction function of Kalman filtering is used to make the algorithm stable in the face of short-term occlusion. The effectiveness of the tracking algorithm proposed in this paper is verified by experiments.