Trajectory tracking of particle material motion on sieve surface based on Mean shift algorithm

For tracking target particles’ motion on air-and-screen cleaning sieve, staining method was used and Mean shift algorithm utilizing the color eigenvector was proposed. Bhattacharyya coefficient was exploited to decide whether the target was occluded. In the frames of regular tracking, the initial point of Mean shift algorithm was predicted by Kalman filter and then the precise position of the target was calculated with Mean shift algorithm. When the occlusion appears, the target motion was regared as a time-invariant system and the position was estimated by Kalman filter. Experiment results show that the algorithm is robust and can track the fast motion target stably with complex background and variant light. The usefull image detection technology was provided for motion law research of granular materials.