基于流行排序的多示例图像检索方法

摘要

为了提高图像检索的性能,提出了一种基于流行排序的多示例图像检索方法,将分割后的图像表示为多示例的形式,通过给出适合图像在包空间的度量方式,有效结合流行排序和多示例学习的方法来进行图像检索.实验结果表明,采用所提出的方法的检索结果与传统的检索方法相比,检索率得到了明显的提高,检索结果更符合人的视觉习惯.%To improve the performance of image retrieval result, a multi-instance retrieval approach based on manifold ranking is proposed. The segmented image is represented under multi-instance learning framework. A novel graph based learning approach to image retrieval using multiple instances is presented, which extends the conventional manifold ranking to multi-instance setting by introducing the adaptive geometric relationship between two bags of instances. The experiments over Corel images have shown that this approach outperforms other methods and is effective for image retrieval.