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Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines

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Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10198))

Abstract

In this paper we explore the use of deep neural networks to analyze semi-structured series of artworks. We train stacked Restricted Boltzmann Machines on the Exactitudes collection of photo series, and use this to understand the relationship between works and series, uncover underlying features and dimensions, and generate new images. The projection of the series on the two major decorrelated features (PCA on top of Boltzmann features) results in a visualization that clearly reflects the semi structured nature of the photos series, although the original features provide better classification results when assigning photographs to series. This work provides a useful case example of understanding structure that is uncovered by deep neural networks, as well as a tool to analyze the underlying structure of a collection of visual artworks, as a very first step towards a robot curator.

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Notes

  1. 1.

    Generated experimental images, including and extending beyond those in this paper, are available for download at high resolution from https://samverkoelen.com/evomusart17/.

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Acknowledgements

We acknowledge Ari Versluis and Ellie Uyttenbroek as the creators of Exactitudes and owners of all intellectual rights and privileges, and are grateful to them for sharing this wonderful collection with the world via www.exactitudes.com.

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Authors and Affiliations

  1. Media Technology Group, Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

    Sam D. Verkoelen, Maarten H. Lamers & Peter van der Putten

Authors
  1. Sam D. Verkoelen
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  2. Maarten H. Lamers
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  3. Peter van der Putten
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Corresponding author

Correspondence to Maarten H. Lamers .

Editor information

Editors and Affiliations

  1. University of Coimbra , Coimbra, Portugal

    João Correia

  2. RMIT University , Melbourne, Victoria, Australia

    Vic Ciesielski

  3. University of Malta , Msida, Malta

    Antonios Liapis

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Verkoelen, S.D., Lamers, M.H., van der Putten, P. (2017). Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines. In: Correia, J., Ciesielski, V., Liapis, A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2017. Lecture Notes in Computer Science(), vol 10198. Springer, Cham. https://doi.org/10.1007/978-3-319-55750-2_22

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  • DOI: https://doi.org/10.1007/978-3-319-55750-2_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55749-6

  • Online ISBN: 978-3-319-55750-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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