MATLAB Simulation of Mean-Shift Moving Target Tracking

This program provides a MATLAB simulation of mean-shift based moving target tracking. The mean-shift algorithm is a widely used target tracking method capable of following targets under complex background conditions. The simulation demonstrates core implementation aspects including target model initialization using color histograms, Bhattacharyya coefficient calculation for similarity measurement, and iterative mean-shift vector computation for target localization. Researchers can use this program to better understand the practical implementation process of the mean-shift algorithm, including how the algorithm handles scale adaptation and occlusion scenarios through kernel density estimation and histogram back-projection techniques. The code structure showcases important MATLAB functions such as histogram equalization, spatial kernel weighting, and convergence criteria implementation. Additionally, this simulation enables researchers to further explore mean-shift algorithm applications across different scenarios, including varying illumination conditions, target scale changes, and partial occlusions. The modular design allows for easy modification of parameters like kernel bandwidth and histogram bins, facilitating experimentation with algorithm improvements. The program serves as both an educational tool for understanding tracking fundamentals and a foundation for extending research into advanced tracking domains, making it a valuable resource for academic research.