一种基于图的多模态随机游走重排序算法

A multimodal graph-based re-ranking through random walk algorithm

为了提高图像检索中的重排序效果,提出了一种基于图的多模态随机游走重排序算法。不同于现有的重排序算法根据检索返回的图像顺序设置图像列表得分序列初值,该算法将多模态融合应用于随机游走算法,避免单一模态获取图像内容的片面性,并利用多模态随机游走方法对返回图像列表得分序列进行初始化,然后利用多模态重排序算法最优化目标函数,对相关参数和得分列表进行迭代更新,从而获得最终重排序后的图像序列。实验显示了所提出的算法具有良好的重排序效果。

To improve the effect of re-ranking algorithms in image retrieval,this paper presented a multimodal graph- based re-ranking through random walk. Different from existing reranking algorithms which set the initial score se-quence value of an image list according to the image sequence returned by retrieval,the proposed method integrated multimodal to acquire more information and employed a multimodal random walk algorithm to initialize the relevance score list of the retrieved images. T h e n,the proposed method optimized the objective function by using a multimodal graph-based reranking algorithm in which an iteration procedure was used to update the parameters and relevance score list . Finally,the retrieved images were reordered according to the relevance score list . Experimental results demonstrate that the proposed reranking algorithm performs better than some other state- of- the-art algorithms.