Visual tracking based on object modeling using probabilistic graphical model
Ping Sheng · Journal of Optoelectronics·laser · 2010
A novel method of object modeling for visual tracking based on local features and probabilistic graphical model is proposed.The tracked object is represented using a collection of regional affine invariant features,among which the spatial constraints are described by a probabilistic graphical model.During tracking,belief propagation algorithm is first applied to infer the state of each feature in spatial domain.Then,the inferred results are employed to construct the proposal sampling function,by which a particle filter is adopted to estimate the target state.To adapt to changes in object appearance,object model will be updated adaptively according to the stability score of the features.The experimental results show that the proposed method can get reliable track even under complex real world conditions.