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Journal of Artificial Intelligence and Soft Computing Research

The Journal of Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

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Autonomous Viewpoint Selection of Robot Based on Aesthetic Evaluation of a Scene

Kai Lan
  • Corresponding author
  • Department of Micro-Nano System Engineering, Nagoya University, Furo-cho, Chikusa-ku, 464-8601 Nagoya, Japan
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Kosuke Sekiyama
  • Department of Micro-Nano System Engineering, Nagoya University, Furo-cho, Chikusa-ku, 464-8601 Nagoya, Japan
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2016-08-10 | DOI: https://doi.org/10.1515/jaiscr-2016-0019


In this paper, we propose an optimal viewpoint selection system for monitoring robots to search for the optimal viewpoint of a scene with the highest aesthetic property. Using the information of the targets, we propose a novel method for predicting human aesthetic sense for a scene. We construct evaluation functions based on certain known composition rules using three factors, namely, target size, visual balance, and composition fitting value. Then a score, which is a reflection of human evaluation, will be obtained using these functions. The optimal viewpoint will be selected from a number of candidates around the target group, by evaluating the aesthetic properties of scenes for each candidate viewpoint. Finally, once the optimal viewpoint is confirmed, path planning and path following controls are implemented for the robots during the moving process.

Keywords: optimal viewpoint selection system; aesthetic evaluation; viewpoint searching


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About the article

Published Online: 2016-08-10

Published in Print: 2016-10-01

Citation Information: Journal of Artificial Intelligence and Soft Computing Research, Volume 6, Issue 4, Pages 255–265, ISSN (Online) 2083-2567, DOI: https://doi.org/10.1515/jaiscr-2016-0019.

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© 2016. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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