Complex Spatial Region Representation and Similar Matching for Multi-Object Image Retrieval

Spatial relationship and structure models play an important role in various computer vision tasks. Many spatial models focus on global relationship modeling and ignore the detail of the internal structure. This will cause a poor performance in capturing discriminative features for a complex multi-object image. In this paper, we present a novel spatial structure model for complex regions with explicit similar measure. Three aspects of our method should be noted in comparison to the previous approaches. First, we propose a detailed layered graph model for representing complex regions, which has complete description performance and even the slight differences among the local objects can be also recognized. We further provide similar matching algorithms for topological structures based on the detailed layered graph model. Finally, an effective retrieval framework is proposed and applied to multi-object image retrieval. Rigorous experimental evaluations on two datasets demonstrate that the proposed method outperforms other prevailing approaches.