Region based Image Retrieval with Query-Adaptive Feature Fusion

CORC > 自动化研究所 > 中国科学院自动化研究所 > 数字内容技术与服务研究中心 > 新媒体服务与管理技术

	Region based Image Retrieval with Query-Adaptive Feature Fusion
	Zhang, Guixuan; Zhang, Shuwu; Zeng, Zhi; Guan, Hu; Wang, Fangxin
	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.
内容类型	会议论文
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.