Mean Shift Algorithm And Particle Filter Algorithm-based Target Tracking

Object tracking have special advantage in the automatic control, scout system,medical science picture identify etc. In recent years, Target tracking technique still can'tattain people's satisfaction, seriously obstructed its application expansion, so it is an urgentproblem to research target tracking. The difficult problem in visual tracking is performingfast and reliable matching of target from frame to frameThe thesis explores currently two kinds of targets tracking algorithm, Mean Shiftalgorithm and Particle Filter algorithm. They are very good algorithm in visual targettracking area. The thesis explores the Detection of Moving Targets, To improve therobustness of visual tracking in complex environments, a novel tracking method based onadaptive fusion and particle filter is proposed, the image color and moving cues areadaptively fused to represent the target observation.The thesis explores an image description method based on second order histogramand increase searching scope to improves robustness of visual tracking. An algorithmbased on kernel histogram particle filter is studied, the dimension of particle is reduced andthe required particle is very few, New algorithm makes the best of middle value of particlefilter, so that the complexity of algorithm is not added.