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Dot to dot, simple or sophisticated: a survey on shape reconstruction algorithms

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Abstract

Dot pattern points are the samples taken from all regions of a 2D object, either inside or the boundary. Given a set of dot pattern points in the plane, the shape reconstruction problem seeks to find the boundaries of the points. These boundaries are not mathematically well-defined. Hence, a superior algorithm is the one which produces the result closest to the human visual perception. There are different challenges in designing these algorithms, such as the independence from human supervision, and the ability to detect multiple components, holes and sharp corners. In this paper, we present a thorough review on the rich body of research in shape reconstruction, classify the ideas behind the algorithms, and highlight their pros and cons. Moreover, to overcome the barriers of implementing these algorithms, we provide an integrated application to visualize the outputs of the prominent algorithms for further comparison.

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Data availability

The application of shape reconstruction which has been implemented by the authors is available at https://github.com/KNTU-CG/dot-to-dot.

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Acknowledgements

The authors would like to express their gratitude to the anonymous reviewers for providing insightful comments which have contributed to improving the quality of presenting the paper.

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  1. Faculty of Computer Engineering, K. N. Toosi University of Technology, Tehran, Iran

    Farnaz Sheikhi, Behnam Zeraatkar & Sama Hanaie

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  1. Farnaz Sheikhi
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Sheikhi, F., Zeraatkar, B. & Hanaie, S. Dot to dot, simple or sophisticated: a survey on shape reconstruction algorithms. Acta Informatica 60, 335–359 (2023). https://doi.org/10.1007/s00236-023-00443-7

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