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On evolutionary computation techniques for multi-view triangulation

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Abstract

Multi-view triangulation is an essential step in recovering three-dimensional structure from a set of images. It is a well-studied problem in computer vision with many suboptimal and optimal methods based on different optimality criteria. In this paper, we assess the ability of evolutionary computation (EC) methods in finding highly accurate solutions to this problem. We use an overlaying Luus–Jaakola optimizer to find good parameter configurations and determine appropriate computational budget for the EC methods. Empirical results on synthetic and real data demonstrate the superior performance of EC methods over existing triangulation methods.

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Acknowledgements

The first author is thankful to the University Grants Commission (UGC) of India for financial support through UGC-JRF fellowship—File No. 15-9(JUNE 2014)/2014(NET), UGC-Ref.No. 3473/(NET-JUNE 2014).

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Authors and Affiliations

  1. Department of Computer Science, Research Centre, University of Kerala, Kariavattom, Kerala, 695581, India

    Nirmal S. Nair

  2. Artificial Intelligence & Computer Vision Lab, Department of Computer Science, Cochin University of Science and Technology, Kochi, Kerala, 682022, India

    Madhu S. Nair

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Nair, N.S., Nair, M.S. On evolutionary computation techniques for multi-view triangulation. Machine Vision and Applications 31, 29 (2020). https://doi.org/10.1007/s00138-020-01077-2

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