关键词: 语义鸿沟, 视觉焦点, WordNet, 词相关性, 图像标注

Abstract: In order to overcome the semantic gap between low-level features and high-level semantic concept of image, an image annotation approach based on visual attention weight and word correlation was proposed. In the process of understanding an image, people pay more attention to focus region. Focus region of an image can be extracted by computing visual attention weight of image regions. The annotation word of focus region is relevant to the annotation word of other image regions, so we can choose proper annotation vector by word correlation. The experimental results show that the new method can improve the precision of image annotation.

Key words: semantic gap, visual attention, WordNet, word correlation, image annotation