Object Tracking Based on Particle Filtering Framework Joint Affine Model and Appearance Model
Pan Jing-feng · Telecommunication Engineering · 2012
An algorithm based on particle filtering framework joint affine model and appearance model is introduced in this paper for object tracking in video sequences.The affine parameters for pose estimation from the corresponding feature points,which are extracted between two successive images,can be formed as a solution to Sylvester's equation.Then,the affine parameters can be smoothly estimated within the particle filtering framework based on the affine group.The state dynamic is modeled via the first order autoregressive(AR) process on the affine group.And the optimal mean state of particles is estimated through the total likelihood function which is a combination of affine feature model and appearance model.Thus,object tracking can be actualized via particle filtering based on the affine group.Experimental results demonstrate the proposed method is more effective and robust compared with other algorithms when the tracked object undergoes pose and scale changes,occlusion and complex background.