Assigning Relative Importance to Scene Elements
The human brain is able to rapidly understand scenes through the recognition of their composing elements and comprehension of the role that each of them plays. This process, related to human perception, impacts in what people care when they see an image and the priority they give to each element. The idea of priority, also referred as importance, is based on biological features of perception and social aspects that interfere in how people perceive what they see and what is considered relevant. In this context, this paper proposes the Element Importance Relative Assignment (EIRA), an approach that models how humans attribute importance to elements in a scene. This approach is based on perceptual, compositional and contextual features employed to assign importance to elements in a scene. To evaluate the proposed approach, tests are conducted in different image datasets with emphasis on the UIUC Pascal Sentence Dataset, where our approach achieves an average accuracy of 86.89%.