Issue No. 03 - July-Sept. (2013 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MMUL.2013.18
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.
Multimedia communication, Image representation, Media, Information retrieval, Image matching, Feature recognition, nested-SIFT, SimHash, multimedia, multimedia applications, feature representation, image matching, image retrieval
P. Xu, L. Zhang, K. Yang and H. Yao, "Nested-SIFT for Efficient Image Matching and Retrieval," in IEEE MultiMedia, vol. 20, no. , pp. 34-46, 2013.