Automatic attention object extraction from images

With the development of content-based multimedia systems, there is a need for automatic extraction of objects from natural images. However, the objects extracted by most existing approaches are often inconsistent with human perception since these approaches totally neglect the viewer's attentions. To address this issue, a method is presented in this paper to automatically extract the viewer's attended objects from an image. Without fully understanding of the semantic content of an image, this method takes advantage of computational attention mechanisms and the seeded region growing technique. It may further facilitate the content-based image/video coding, indexing, and retrieval. Preliminary experimental evaluations on 200 real images demonstrate the effectiveness of this method.