Forest hashing: Expediting large scale image retrieval

Abstract

This paper introduces a hybrid method for searching large image datasets for approximate nearest neighbor items, specifically SIFT descriptors. The basic idea behind our method is to create a serial system that first partitions approximate nearest neighbors using multiple kd-trees before calling upon locally designed spectral hashing tables for retrieval… (More)
DOI: 10.1109/ICASSP.2013.6637938

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Cite this paper

@article{Springer2013ForestHE, title={Forest hashing: Expediting large scale image retrieval}, author={Jonathan Springer and Xin Xin and Zhu Li and Jeremy Watt and Aggelos K. Katsaggelos}, journal={2013 IEEE International Conference on Acoustics, Speech and Signal Processing}, year={2013}, pages={1681-1684} }