In this paper we evaluate performance of data-dependent hashing methods on binary data. The goal is to find a hashing method that can effectively produce lower dimensional binary representation of 512-bit FREAK descriptors. A representative sample of recent unsupervised, semi-supervised and supervised hashing methods was experimentally evaluated on large datasets of labelled binary FREAK feature descriptors.
@article{arxiv.1707.06825,
title = {Evaluation of Hashing Methods Performance on Binary Feature Descriptors},
author = {Jacek Komorowski and Tomasz Trzcinski},
journal= {arXiv preprint arXiv:1707.06825},
year = {2017}
}