Effective near-duplicate image retrieval with image-specific visual phrase selection

Near-duplicate image retrieval (NDIR) is an important topic for many applications such as multimedia content management, copyright infringement identification et al. In this work we propose a novel NDIR framework based on visual phrase. Compared with previous researches, this paper first introduces a spatial visual phrase (SVP) model enabling to capture relative geometry information between visual words. Then, it proposes an image-specific strategy to select descriptive SVPs. The strategy can not only handle the phrase sparseness problem which occurs in traditional selection strategy but also allow to select visual phrases according to the characteristic of each image. Experiments are carried out over Ukbench dataset and TRECVID dataset respectively, and encouraging experimental results demonstrate that both the SVP model and the selection strategy significantly improve the overall performance.