Region matching and similarity enhancing for image retrieval
Guixuan Zhang; Zhi Zeng; Shuwu Zhang; Hu Guan; Qinzhen Guo
Conference NameIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Conference Date2016年3月20日-3月25日
Conference Place上海
AbstractMany image retrieval systems adopt the bag-of-words model and rely on matching of local descriptors. However, these descriptors of keypoints, such as SIFT, may lead to false matches, since they do not consider the contextual information of the keypoints. In this paper, we incorporate the cues of meaningful regions where local descriptors are extracted. We describe a matching region estimation (MRE) method to find appropriate matching regions for local descriptor matching pairs. Then the region matching quality is evaluated and the true matched regions will enhance the similarity of local descriptors. Consequently, the image retrieval accuracy can be improved. Extensive experiments on benchmark datasets show the effectiveness of our method and our result compares favorably with the state-of-the-art.
KeywordMatching Region Estimation Similarity Enhancing Fisher Vector Regional Clues Image Retrieval
Indexed ByEI
Document Type会议论文
AffiliationInstitute of Automation, Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Guixuan Zhang,Zhi Zeng,Shuwu Zhang,et al. Region matching and similarity enhancing for image retrieval[C],2016.
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