Computational visual attention model capable of exploring similarity

Computational visual attention (CVA) model is one of the methods which focus on finding region of interesting (ROI) in an image or in a scene. Similarity attention is one important task in CVA. If there are many objects in a scene, people will pick up the most abnormal one, which perhaps the similar one or dissimilar one, according to the composition objects of the scene. Capability of similarity attention enables human vision to promptly focus on similar or dissimilar regions in a scene. This paper implements this capability in the CVA model by attaching a high-level similarity comparison function to find ROI in the scene. The output of the model simulates the serial search mode and more approach to human visual behavior. Experimental results show that the function of similarity attention can be achieved successfully.