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Fast and Robust Point-in-Spherical-Polygon Tests Using Multilevel Spherical Grids

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10582))

Abstract

Point-in-spherical-polygon determination is widely required in applications over the earth. However, existing methods for point-in-polygon tests cannot be applied directly, due to non-Euclidean computation over the spherical surface. Thus, it is general to transform a spherical polygon into a planar polygon via projection, and then perform point-in-polygon tests. Unfortunately, this is expensive and may cause determination errors. In this paper, we propose to subdivide the spherical grid cells iteratively, and apply the ray-crossing method locally in grid cells, which is by one of our previous works. As a result, this not only avoids expensive transformation computation, but also guarantees robust determination for point-in-spherical-polygon tests. Experimental results attest our effectiveness, and show an acceleration of five orders of magnitude over a popularly used method.

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References

  1. Raskin, R.G.: Spatial analysis on the sphere. Technical report 94-7. University of California, Santa Barbara (1994)

    Google Scholar 

  2. Bevis, M., Chatelain, J.-L.: Locating a point on a spherical surface relative to a spherical polygon of arbitrary shape. Math. Geol. 21(8), 811–828 (1989)

    Article  Google Scholar 

  3. Nedrich, M., Davis, W.J.: Detecting behavioral zones in local and global camera views. Mach. Vis. Appl. 24, 579–605 (2013)

    Article  Google Scholar 

  4. Bello, L., Coltice, N., Tackley, P.J., Muller, R.D., Cannon, J.: Assessing the role of slab rheology in coupled plate-mantle convention models. Earth Planet. Sci. Lett. 430, 191–201 (2015)

    Article  Google Scholar 

  5. Li, J., Wang, W.-C.: Fast and robust GPU-based point-in-polyhedron determination. Comput. Aided Des. 87, 20–28 (2017)

    Article  Google Scholar 

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Acknowledgment

This work is partially supported by the sub-project of the National Key Research and Development Program of China (No. 2016QY01W0101), the National Natural Science Foundation of China (Nos. 60873182, 61379087, U1435220, and 61661146002), and the EU FP7 funded project AniNex (FP7-IRSES-612627).

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Correspondence to Jing Li .

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Li, J., Zhang, H., Wang, W. (2017). Fast and Robust Point-in-Spherical-Polygon Tests Using Multilevel Spherical Grids. In: Chang, J., Zhang, J., Magnenat Thalmann, N., Hu, SM., Tong, R., Wang, W. (eds) Next Generation Computer Animation Techniques. AniNex 2017. Lecture Notes in Computer Science(), vol 10582. Springer, Cham. https://doi.org/10.1007/978-3-319-69487-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-69487-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69486-3

  • Online ISBN: 978-3-319-69487-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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