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Using Deep Autoencoders to Investigate Image Matching in Visual Navigation

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Biomimetic and Biohybrid Systems (Living Machines 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10384))

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Abstract

This paper discusses the use of deep auto encoder networks to find a compressed representation of an image, which can be used for visual navigation. Images reconstructed from the compressed representation are tested to see if they retain enough information to be used as a visual compass (in which an image is matched with another to recall a bearing/movement direction) as this ability is at the heart of a visual route navigation algorithm. We show that both reconstructed images and compressed representations from different layers of the auto encoder can be used in this way, suggesting that a compact image code is sufficient for visual navigation and that deep networks hold promise for finding optimal visual encodings for this task.

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Acknowledgements

This work was funded by the Newton Agri-Tech Program RICE PADDY project (no. STDA00732). AP and PG were also funded by EPSRC grant EP/P006094/1.

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Authors and Affiliations

  1. Department of Informatics, Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, UK

    Christopher Walker & Andrew Philippides

  2. School of Life Sciences, Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, UK

    Paul Graham

Authors
  1. Christopher Walker
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  2. Paul Graham
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  3. Andrew Philippides
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Corresponding author

Correspondence to Andrew Philippides .

Editor information

Editors and Affiliations

  1. University of Lincoln, Lincoln, United Kingdom

    Michael Mangan

  2. Stanford University, Stanford, California, USA

    Mark Cutkosky

  3. Universitat Pompeu Fabra, Barcelona, Spain

    Anna Mura

  4. Universitat Pompeu Fabra, Barcelona, Spain

    Paul F.M.J. Verschure

  5. University of Sheffield, Sheffield, United Kingdom

    Tony Prescott

  6. Bristol University, Bristol, United Kingdom

    Nathan Lepora

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Walker, C., Graham, P., Philippides, A. (2017). Using Deep Autoencoders to Investigate Image Matching in Visual Navigation. In: Mangan, M., Cutkosky, M., Mura, A., Verschure, P., Prescott, T., Lepora, N. (eds) Biomimetic and Biohybrid Systems. Living Machines 2017. Lecture Notes in Computer Science(), vol 10384. Springer, Cham. https://doi.org/10.1007/978-3-319-63537-8_39

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  • DOI: https://doi.org/10.1007/978-3-319-63537-8_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63536-1

  • Online ISBN: 978-3-319-63537-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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