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SPHORB: A Fast and Robust Binary Feature on the Sphere

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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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Notes

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

  2. 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.

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

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Acknowledgments

The authors thank all reviewers and the associate editor for their valuable comments. The authors also thank Chu Han, Wuyao Shen, and Xiangyu Mao for capturing CUHK dataset used in Table 1. The work was supported by the National Natural Science Foundation of China (61100122 and 61100121), New Century Excellent Talents in University (NCET-11-0365), the National Science and Technology Support Project (2013BAK01B01 and 2014BAK09 B04), Tianjin Science Foundation for Youth (12JCQNJC00100), and the research Fund from The Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China (TJKLASP-2012-2).

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Authors and Affiliations

  1. School of Computer Science & Technology, Tianjin University, Tianjin, China

    Qiang Zhao & Wei Feng

  2. School of Computer Software, Tianjin University, Tianjin, China

    Liang Wan & Jiawan Zhang

  3. Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin, China

    Liang Wan

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  1. Qiang Zhao
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  2. Wei Feng
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  3. Liang Wan
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  4. Jiawan Zhang
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Correspondence to Liang Wan.

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Communicated by Jiri Matas.

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Zhao, Q., Feng, W., Wan, L. et al. SPHORB: A Fast and Robust Binary Feature on the Sphere. Int J Comput Vis 113, 143–159 (2015). https://doi.org/10.1007/s11263-014-0787-4

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  • DOI: https://doi.org/10.1007/s11263-014-0787-4

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