Relative Influence of Bottom-Up and Top-Down Attention

Attention and memory are very closely related and their aim is to simplify the acquired data into an intelligent structured data set. Two main points are discussed in this paper. The first one is the presentation of a novel visual attention model for still images which includes both a bottom-up and a top-down approach. The bottom-up model is based on structures rarity within the image during the forgetting process. The top-down information uses mousetracking experiments to build models of a global behavior for a given kind of image. The second interesting point is that the relative importance of bottom-up and top-down information depends on the specificity of each image. For the three different sets of images within the database the importance of the topdown information is different. The proposed models assessment is achieved on a 91-image database.