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Nested-SIFT for Efficient Image Matching and Retrieval
July-Sept. 2013 (vol. 20 no. 3)
pp. 34-46
Pengfei Xu, Harbin Institute of Technology, China
Lei Zhang, Microsoft Research Asia
Kuiyuan Yang, Microsoft Research Asia
Hongxun Yao, Harbin Institute of Technology, China
To improve the effectiveness of feature representation and the efficiency of feature matching, we propose a new feature representation, named Nested-SIFT, which utilizes the nesting relationship between SIFT features to group local features. A Nested-SIFT group consists of a bounding feature and several member features covered by the bounding feature. To obtain a compact representation, SimHash strategy is used to compress member features in a Nested-SIFT group into a binary code, and the similarity between two Nested-SIFT groups is efficiently computed by using the binary codes. Extensive experimental results demonstrate the effectiveness and efficiency of our proposed Nested-SIFT approach.
Index Terms:
Multimedia communication,Image representation,Media,Information retrieval,Image matching,Feature recognition,nested-SIFT,SimHash,multimedia,multimedia applications,feature representation,image matching,image retrieval
Citation:
Pengfei Xu, Lei Zhang, Kuiyuan Yang, Hongxun Yao, "Nested-SIFT for Efficient Image Matching and Retrieval," IEEE Multimedia, vol. 20, no. 3, pp. 34-46, July-Sept. 2013, doi:10.1109/MMUL.2013.18
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