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International Journal of Computer Vision

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01-06-2015

SPHORB: A Fast and Robust Binary Feature on the Sphere

Authors: Qiang Zhao, Wei Feng, Liang Wan, Jiawan Zhang

Published in: International Journal of Computer Vision | Issue 2/2015

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Abstract

In this paper, we propose SPHORB, a new fast and robust binary feature detector and descriptor for spherical panoramic images. In contrast to state-of-the-art spherical features, our approach stems from the geodesic grid, a nearly equal-area hexagonal grid parametrization of the sphere used in climate modeling. It enables us to directly build fine-grained pyramids and construct robust features on the hexagonal spherical grid, thus avoiding the costly computation of spherical harmonics and their associated bandwidth limitation. We further study how to achieve scale and rotation invariance for the proposed SPHORB feature. Extensive experiments show that SPHORB consistently outperforms other existing spherical features in accuracy, efficiency and robustness to camera movements. The superior performance of SPHORB has also been validated by real-world matching tests.

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There exist binary descriptors that are not generated by intensity comparison, e.g. LDAHash (Strecha et al. 2012).

A direct workaround may be rotating the panorama so that the pentagons cover different regions of the original panorama and the transformed one. Then the keypoints from the transformed panorama are taken as the complements after removing the reduplicative keypoints.

https://sites.google.com/site/javicm/software.

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Title: SPHORB: A Fast and Robust Binary Feature on the Sphere
Authors: Qiang Zhao
Wei Feng
Liang Wan
Jiawan Zhang
Publication date: 01-06-2015
Publisher: Springer US
Published in: International Journal of Computer Vision / Issue 2/2015
Print ISSN: 0920-5691
Electronic ISSN: 1573-1405
DOI: https://doi.org/10.1007/s11263-014-0787-4

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