Automatic Object Extraction Using Hierarchical Semantic Model

A new hierarchical semantic model method is proposed to overcome the disadvantages existing in most of the relative methods.Firstly,a multi-scale segmentation is employed to obtain the candidate object regions.Secondly,semantic model is utilized to get objects semantic distribution information.Lastly,in the extraction processing stage,a correlative function based on the semantic model and the candidate object regions is built up and maximized to extract the objects.Experimental results demonstrate the precision,robustness,and effectiveness of the proposed method.