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eSphere: extracting spheres from unorganized point clouds

How to extract multiple spheres accurately and simultaneously

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Abstract

Spheres are popular geometric primitives found in many manufactured objects. However, sphere fitting and extraction have not been investigated in depth. In this paper, a robust method is proposed to extract multiple spheres accurately and simultaneously from unorganized point clouds. Moreover, a novel validation step is presented to assess the quality of the detected spheres, which help remove the confusion between perfect spheres and sphere-like shapes such as ellipsoids and paraboloids. A novel sampling strategy is introduced to reduce computational burden for sphere extraction. Experiments on both synthetic and scanned point clouds with different levels of noise and outliers are conducted and the results compared to state-of-the-art methods. These experiments demonstrate the efficiency and robustness of the proposed sphere extraction method.

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Acknowledgments

This research project was supported by the NSERC/Creaform Industrial Research Chair on 3-D Scanning. The authors express their gratitude to Kean Walmsley at Autodesk for providing the Sphere Packing model, to 3D Warehouse for making the Carbon Nano Tube and ADN models available (Fig. 19) and to GrabCAD for the bracelet model (Fig. 16). We are grateful to our colleagues, Jean-Francois Lalonde and to the anonymous reviewers for fruitful suggestions and to Annette Schwerdteger for proofreading the manuscript.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Laval University, Quebec, G1V 0A6, Canada

    Trung-Thien Tran, Van-Toan Cao & Denis Laurendeau

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  1. Trung-Thien Tran
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  2. Van-Toan Cao
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  3. Denis Laurendeau
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Correspondence to Trung-Thien Tran.

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Tran, TT., Cao, VT. & Laurendeau, D. eSphere: extracting spheres from unorganized point clouds. Vis Comput 32, 1205–1222 (2016). https://doi.org/10.1007/s00371-015-1157-0

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