A Moving Target Tracking Method Based on Particle Filter and Mean-shift

Abstract

Due to the limitation of using a single algorithm Mean-shift or particle filter, the deterministic tracker Mean-shift is introduced into the framework of particle filter, and a new hybrid tracking method based on particle filter and Mean-shift is proposed. The tracking method first uses Dynamic K-Means Soft Clustering algorithm to cluster multiple hypotheses, and then carries out Mean-shift deterministic search for the centers of clusters. The tracking experiments show that the proposed method can perform well when the target changes, rotates and scales, and achieves a satisfactory tracking speed.