计算机工程2011，Vol.37Issue(13)：17-19,25,4.DOI:10.3969/j.issn.1000-3428.2011.13.005
一种用于复杂目标感知的视觉注意模型
Visual Attention Model for Complex Target Perception
摘要
Abstract
A new visual attention model used for rapid perception of complex targets in natural scene is proposed. In the learning process, the model extracts saliency blobs from a given target's image. Then during the process of attention on a scene image, it adopts a blob searching and merging strategy based on graph matching to guide visual focus to where it looks like the target. The blob searching and merging strategy uses features of learned heterogeneous blobs and their spatial relative positions, which are all recorded during the previous target learning process.Compared with typical bottom-up visual attention model, experiments show that the new method could efficiently introduce feature and structure information of complex target into the process of attention, reduce useless visual focus shifts, and improve the performance of visual attention. The model could be used to locate complex structural targets in natural scene images.关键词
视觉注意模型/视觉搜索/显著性图斑/目标感知/图像匹配Key words
visual attention model/ visual search/ saliency blob/ target perception/ image matching分类
信息技术与安全科学引用本文复制引用
暴林超,蔡超,肖洁,周成平..一种用于复杂目标感知的视觉注意模型[J].计算机工程,2011,37(13):17-19,25,4.基金项目
国家"863"计划基金资助项目(2007AA12Z166) （2007AA12Z166）
