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.
CITATION STYLE
Komorowski, J., & Trzciński, T. (2018). Evaluation of hashing methods performance on binary feature descriptors. In Advances in Intelligent Systems and Computing (Vol. 681, pp. 88–98). Springer Verlag. https://doi.org/10.1007/978-3-319-68720-9_12
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