Summary. 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.
REF investigates if data-dependent hashing methods can be applied to find more compact representation of binary feature descriptors.
Evaluation of Hashing Methods Performance on Binary Feature Descriptors
ArXiv
ArXiv
Computer Science