基于视觉显著计算的图像语义检索方法

Image Semantic Retrieval Based on Visual Saliency Computation

网络标签已经开始广泛地用于图像内容的标注和分享,由于图像本身的差异和人们对图像的不同理解,对图像语义检索提出了新的挑战。该文首先引入视觉显著模型,突出图像的显著信息;然后提取视觉显著特征,建立图像内容的相似关系;最后基于随机漫步模型平衡图像内容及网络标签间的关系。实验表明该文提出的方法能够有效地实现图像的语义理解并用于图像检索。

Internet labeling and tags have been used extensively to describe the image contents on the Web.To understand and utilize these tags for image semantic retrieval,this paper introduces a visual saliency model to emphasize the salient information,and then,extracts the visual feature to describe the similarity between images.At last,a novel random walk is proposed to balance the influences between the image contents and tags.Experiments show the effectiveness and feasibility of the proposed method when applied in image understanding and retrieval.