Region based Image Retrieval with Query-Adaptive Feature Fusion
文献类型：会议论文
| 作者 | Zhang, Guixuan ; Zhang, Shuwu; Zeng, Zhi; Guan, Hu; Wang, Fangxin
|
| 出版日期 | 2017 |
| 会议日期 | 17-20 September 2017 |
| 会议地点 | CNCC, Beijing, China |
| 关键词 | Image Retrieval Convolutional Neural Networks Fisher Vector Feature Fusion |
| 英文摘要 | Recently, image representation based on convolutional neural network (CNN) becomes more popular than SIFT based feature, such as Fisher vector (FV). However, which of the two works better for image retrieval is not entirely clear yet. In this paper, we propose to fuse CNN and FV to incorporate the advantages of both features for image retrieval. We extract CNN feature and FV from multi-scale regions, which makes the representation more robust to image noise. Then a query-adaptive feature fusion method is proposed, which is used jointly with 2-D inverted index under the framework of bag-of-words. Moreover, we make an evaluation of different CNN feature extraction methods for the region based method. Extensive experiments on four benchmark datasets demonstrate the effectiveness of our method with efficiency in both time cost and memory usage. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/15411]  |
| 专题 | 数字内容技术与服务研究中心_新媒体服务与管理技术 |
| 作者单位 | Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Zhang, Guixuan,Zhang, Shuwu,Zeng, Zhi,et al. Region based Image Retrieval with Query-Adaptive Feature Fusion[C]. 见:. CNCC, Beijing, China. 17-20 September 2017. |
入库方式： OAI收割
来源：自动化研究所
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