PARTICLE FILTERS BASED VISUAL OBJECT TRACKING

Abstract

This dissertation is concerned with the tracking of an object of interest in the video and analysis of different parameters with reference to the record of trajectories over the frames apart from the rigorous treatment of Particle filter theory. In this dissertation, rigorous mathematical aspects and various algorithms of Particle filters have been discussed with MATLAB simulation results. Comparisons of Sequential Importance Resampling (SIR) Particle filter, Auxiliary Particle filter (APF) and Gaussian Particle filter (GPF) in terms of Mean Square Error (MSE) have also been simulated using MATLAB along with their states and estimate states for univariate non-stationary growth. Conditional linearity in the dynamic nonlinear system under the Rao-Blackwell Particle filter has also been simulated using MATLAB for tracking a maneuvering target along with its comparison with particle filter. Under visual object tracking part, an SIR Particle filter based tracking of an object of interest in the video has been simulated using two methods such as, intensity histogram and color histogram. The shape of the object is modeled as an ellipse, along which an intensity gradient is estimated, while the interior appearance is modeled using a color histogram. MATLAB simulation shows the Belief states over the frames with handling of visual clutter along with the visual object trajectory, HSV cdf, and 3D histogram of target distribution. Other simulation shows the prediction of object position, bounding ellipse particles, posterior distribution of the moving object over the frames and SIR resampling of the tracked object. The results show that Color histogram based particle filter tracking is robust to partial occlusion, rotation, scaling, and changes in illumination and pose. Performance of the Particle filtering tracking can also be improved by using more particles. Results also show that the tracking method is able to keep track for a fairly long time, despite the presence of clutter.