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Object Annotation Based on Middle Semantic Manifold

A novel bionic, middle semantic object annotation framework is presented in this paper. Moreover, we build the model based on the perception as defined by the human visual system. At first, the super-pixel is used to represent the images, and conditional random field could label each of the super-pixels, which means annotating the different classes of objects. In next step, on the basis of the previous result, image pyramid is used to represent the image, and get the sub-region of some objects of the same class. After extracting descriptor to represent the patches, all the patches are projected to a manifold, which could annotate the different views of objects from the same class. Experiments show that the bionic, middle semantic object annotation framework could obtain superior results with respect to accuracy.