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Optimal Viewpoint Selection Based on Aesthetic Composition Evaluation Using Kullback-Leibler Divergence

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Intelligent Robotics and Applications (ICIRA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9834))

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Abstract

In this paper, we construct a robot photographic system to search for the optimal viewpoint of a scene. Based on some known composition rules in the field of photography, we propose a novel aesthetic composition evaluation method by the use of Kullback-Leilber divergence. For viewpoint selection, we put forward a method called Composition-map, which can estimate the aesthetic value of scenes for each candidate viewpoint around the target group. At last, the effectiveness of our robot photographic system is confirmed with practical experiments.

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References

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Author information

Authors and Affiliations

  1. Department of Micro-Nano System Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan

    Kai Lan & Kosuke Sekiyama

Authors
  1. Kai Lan
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  2. Kosuke Sekiyama
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Corresponding author

Correspondence to Kai Lan .

Editor information

Editors and Affiliations

  1. Tokyo Metropolitan University , Tokyo, Japan

    Naoyuki Kubota

  2. Kyushu University , Fukuoka, Japan

    Kazuo Kiguchi

  3. University of Portsmouth , Portsmouth, United Kingdom

    Honghai Liu

  4. Tokyo Metropolitan University , Tokyo, Japan

    Takenori Obo

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Lan, K., Sekiyama, K. (2016). Optimal Viewpoint Selection Based on Aesthetic Composition Evaluation Using Kullback-Leibler Divergence. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9834. Springer, Cham. https://doi.org/10.1007/978-3-319-43506-0_38

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  • DOI: https://doi.org/10.1007/978-3-319-43506-0_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43505-3

  • Online ISBN: 978-3-319-43506-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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