一种基于结构学习的图像标注方法
首发时间:2013-01-09
摘要:图像标注工作对于当前的基于关键词的图像检索系统至关重要。本文中,我们将图像标注问题看作一个最优子集选择的问题,并通过结构学习的框架来学习一个得分函数,利用该函数来评估不同候选标注集合的质量。一个标注集合的质量由它与待标注图像的视觉近邻图像的多种关系来判定。在基准数据集上的实验结果证明了该方法在图像标注任务中的有效性。
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Image Annotation via Structural Learning
Abstract:Image annotation plays an important role in modern keyword-based image retrieval systems. In this paper, we formulate the image annotation problem as that of selecting the optimal keyword subset for an image, and employ a structural learning framework to learn a scoring function for evaluating the quality of different candidate subsets. The quality of a keyword subset is assessed based on its relations with visually similar neighbors of that image. Experiments on benchmark data set demonstrate the effectiveness of our approach for image annotation.
Keywords: computer applied technology image annotation structural learning
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