HBD: Hexagon-Based Binary Descriptors

Yuan Liu, J. Paul Siebert

2016

Abstract

In this paper, two new rotationally invariant hexagon-based binary descriptors (HBD), i.e., HexIDB and HexLDB, are proposed in order to obtain better feature discriminability while encoding less redundant information. Our new descriptors are generated based on a hexagonal grouping structure that improves upon the HexBinary descriptor we reported previously. The third level descriptors of HexIDB and HexLDB have 270 bits and 99 bits respectively fewer than that of SHexBinary, due to sampling 61% fewer fields. Using learned parameters, HBD demonstrates better performance when matching the majority of the images in Mikolajczyk and Scmidt’s standard benchmark dataset, as compared to existing benchmark descriptors. Moreover, HBD also achieves promising level of performance when applied to pose estimation using the ALOI dataset, achieving  0.5 pixels mean pose error, only slightly inferior to fixed-scale SIFT, but around 1.5 pixels better than standard SIFT.

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Paper Citation


in Harvard Style

Liu Y. and Siebert J. (2016). HBD: Hexagon-Based Binary Descriptors . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 175-182. DOI: 10.5220/0005720401750182


in Bibtex Style

@conference{visapp16,
author={Yuan Liu and J. Paul Siebert},
title={HBD: Hexagon-Based Binary Descriptors},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={175-182},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005720401750182},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)
TI - HBD: Hexagon-Based Binary Descriptors
SN - 978-989-758-175-5
AU - Liu Y.
AU - Siebert J.
PY - 2016
SP - 175
EP - 182
DO - 10.5220/0005720401750182