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Large Visual Repository Search with Hash Collision Design Optimization
April-June 2013 (vol. 20 no. 2)
pp. 62-71
Xin Xin, Samsung Research America and Northwestern University
Abhishek Nagar, Samsung Research America
Gaurav Srivastava, Samsung Research America
Zhu Li, Samsung Research America
Felix Fernandes, Samsung Research America
Aggelos K. Katsaggelos, Northwestern University
Visual search over large image repositories in real time is one of the key challenges for applications such as mobile visual query-by-capture, augmented reality, and biometrics-based identification. Search accuracy and response speed are two important performance factors. This article focuses on one of the important elements of this technology that enables large-scale visual search: indexing (or hashing). Indexing is the process of organizing a database of searchable elements into an efficiently searchable configuration. The searchable elements in our case are compact features extracted from images. This article explores a new indexing scheme. The authors optimize the design of a hash-code collision and counting scheme to enable fast search of visual features of MPEG CDVS.
Index Terms:
Real time systems,Visualization,Search methods,LIbraries,Augmented reality,Biometrics,Image processing,Query processing,CDVS,multimedia,multimedia applications,large-scale visual search,indexing,hash-code collision,mobile search,MPEG
Citation:
Xin Xin, Abhishek Nagar, Gaurav Srivastava, Zhu Li, Felix Fernandes, Aggelos K. Katsaggelos, "Large Visual Repository Search with Hash Collision Design Optimization," IEEE Multimedia, vol. 20, no. 2, pp. 62-71, April-June 2013, doi:10.1109/MMUL.2013.22
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