Abstract:

To deal with the target occlusion problem and illumination changes in moving target tracking, a particle filtering algorithm based on compressive sensing is proposed. The extracted features are added by compressive sense of the improved compressive tracking (CT) algorithm into the framework of particle filtering tracking. The credibility of extracted features including the color features of original particle filtering and compressive sensing features is judged, which deals with the target occlusion effects and illumination changes. The algorithm is tested in public database and experimental results show that the proposed algorithm brings about better robustness and tracks targets accurately in real time in comparison with the improved CT algorithm and particle filtering algorithm.