Multi-feature Extraction and Stepwise Refinement Based High-speed Moving Target Tracking Algorithm

The traditional high-speed moving target tracking schemes can only use image features description constantly, but not adaptively choose the optimal tracking feature according to tracking scenes, which leads to the feature template drift easily.To solve the above problem, a new tracking algorithm of high-speed moving targets based on multi-feature fusion and stepwise refinement is presented.This algorithm consists of three stages:the first stage is the adaptive multi feature fusion stage, through the calculation of target tracking of foreground and background for each feature discrimination, fusion model acquisition target feature;the second stage is the feature tracking based on kernel stage, in the Mean-Shift framework, using Epanechnikov function as the kernel function of pixel weight lifting the ratio of target area center;adaptive updates for the third phase of the target model, through the design of a template updating strategy to improve the accuracy of tracking results.The simulation results show that the proposed algorithm is suitable to track a high-speed target.