Object Recognition Based on Improved Context Model

An object recognition method is proposed in this paper by introducing the spatial location relationship of objects into the context model. The spatial-position information of the objects is first utilized to model the context model. The model parameters and dependency structure of objects can be learned by integrating the context information into the same probabilistic framework. The image recognition is accomplished by using the advantages of efficient inference of the tree structure model. The proposed method can greatly improve the object recognition rate and better keep the consistency of scenes. The effectiveness of the proposed algorithm is verified by testing and comparing with other existing algorithms in the actual dataset.