Hierarchical Image Retrieval by Multi-Feature Fusion

@inproceedings{Lu2017HierarchicalIR,
  title={Hierarchical Image Retrieval by Multi-Feature Fusion},
  author={Xiaojun Lu and Jiaojuan Wang and Ying Hou and Mei Yang and Qi Wang and Xiangde Zhang},
  year={2017}
}
Aiming at the problems that are poor generalization performance, low retrieval accuracy and large time consumption of existing content-based image retrieval system, the hierarchical image retrieval method based on multi feature fusion is proposed in this paper. The retrieval accuracy rates on Corel5K, UKbeach and Holidays are 68.23(Top 1), 3.73(N-S) and 88.20(mAp), respectively. The experimental results show that the method proposed in this paper can effectively improve the deficiency of single… 
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Social Neighborhood Graph and Multigraph Fusion Ranking for Multifeature Image Retrieval
TLDR
A theoretical proof is given to illustrate the role of independent features in improving the retrieval results of multifeature fusion ranking methods and proposes a reranking method named N3G to improve the original ranking list by a single feature.

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