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Vision-based navigation of an unmanned surface vehicle with object detection and tracking abilities

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Abstract

The paper discusses autocalibration, object detection, and object tracking for unmanned surface vehicles. Input data are recorded with a wide-baseline stereo vision system providing accuracy for distance estimations. The paper reports about followed ways and novel contributions for ensuring a working system solution. Automatic self-calibration is used for the wide-baseline stereo vision system. Robust sea surface estimation and the detection of the horizon support the understanding of the given scene environment. Long-range (i.e. up to 500 m) object detection and tracking are supported by the used wide-baseline stereo system. The paper informs about the complete system design, informs about applied or designed methods, and also about experiments which verify that the system achieved an operational state.

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Notes

  1. Due to the extreme difficulties in handling such a very large checkerboard with a crane, etc., we had to limit experiments to a representative set of scenarios.

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Acknowledgements

The authors thank students at NTU Singapore who took part in the USV project, and Singapore Technologies Electronic Ltd. for project support, and Prof. Reinhard Klette for discussions related to different parts of the project.

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Authors and Affiliations

  1. Institute for Software Convergence, Hanyang University, Seoul, Korea

    Bok-Suk Shin

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore

    Xiaozheng Mou & Han Wang

  3. GM Cruise LLC, San Francisco, CA, USA

    Wei Mou

Authors
  1. Bok-Suk Shin
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  2. Xiaozheng Mou
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  3. Wei Mou
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  4. Han Wang
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Correspondence to Bok-Suk Shin.

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Shin, BS., Mou, X., Mou, W. et al. Vision-based navigation of an unmanned surface vehicle with object detection and tracking abilities. Machine Vision and Applications 29, 95–112 (2018). https://doi.org/10.1007/s00138-017-0878-7

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  • DOI: https://doi.org/10.1007/s00138-017-0878-7

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