A non-linear camera calibration with modified teaching-learning-based optimization algorithm

Buyang Zhang; Hua Yang; Shuo Yang

doi:10.1117/12.2228597

9 December 2015 A non-linear camera calibration with modified teaching-learning-based optimization algorithm

Buyang Zhang, Hua Yang, Shuo Yang

Proceedings Volume 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015); 981714 (2015) https://doi.org/10.1117/12.2228597
Event: Seventh International Conference on Graphic and Image Processing, 2015, Singapore, Singapore

Abstract

In this paper, we put forward a novel approach based on hierarchical teaching-and-learning-based optimization (HTLBO) algorithm for nonlinear camera calibration. This algorithm simulates the teaching-learning ability of teachers and learners of a classroom. Different from traditional calibration approach, the proposed technique can find the nearoptimal solution without the need of accurate initial parameters estimation (with only very loose parameter bounds). With the introduction of cascade of teaching, the convergence speed is rapid and the global search ability is improved. Results from our study demonstrate the excellent performance of the proposed technique in terms of convergence, accuracy, and robustness. The HTLBO can also be used to solve many other complex non-linear calibration optimization problems for its good portability.

Citation Download Citation

Buyang Zhang, Hua Yang, and Shuo Yang "A non-linear camera calibration with modified teaching-learning-based optimization algorithm", Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 981714 (9 December 2015); https://doi.org/10.1117/12.2228597

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