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Composition Improvement for Portrait Photographs

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Computational Approaches in the Transfer of Aesthetic Values from Paintings to Photographs

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Abstract

Composition has a great impact upon the visual quality of a photograph. This chapter studies the composition in portrait paintings and proposes an algorithm to improve the composition of portrait photographs based on an example portrait painting. From a study of portrait painting, it can be shown that the placement of the face and the figure in portrait paintings is pose-related. Based on this observation, our algorithm improves the composition of a portrait photograph by referencing the placement of the face and the figure from an example portrait painting. The example portrait painting is selected based on the similarity of its figure pose to that of the input photograph. This similarity measure is modelled as a graph matching problem. Finally, space cropping is performed using an optimisation function to assign a similar location for each body part of the figure in the photograph with that in the example portrait painting. The experimental results demonstrate the effectiveness of the proposed method. A user study shows that the proposed pose-based composition improvement is preferred more than the rule-based methods.

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Authors and Affiliations

  1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

    Xiaoyan Zhang

  2. Royal Melbourne Institute of Technology, Ho Chi Minh, Vietnam

    Martin Constable

  3. Tolendata Singapore R&D Centre Pvt. Ltd., Singapore, Singapore

    Kap Luk Chan

  4. Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

    Jinze Yu

  5. University of Southern California, Los Angeles, CA, USA

    Wang Junyan

Authors
  1. Xiaoyan Zhang
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  2. Martin Constable
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  3. Kap Luk Chan
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  4. Jinze Yu
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  5. Wang Junyan
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Correspondence to Xiaoyan Zhang .

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© 2018 Springer Nature Singapore Pte Ltd.

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Zhang, X., Constable, M., Chan, K.L., Yu, J., Junyan, W. (2018). Composition Improvement for Portrait Photographs. In: Computational Approaches in the Transfer of Aesthetic Values from Paintings to Photographs. Springer, Singapore. https://doi.org/10.1007/978-981-10-3561-6_8

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  • DOI: https://doi.org/10.1007/978-981-10-3561-6_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3559-3

  • Online ISBN: 978-981-10-3561-6

  • eBook Packages: EngineeringEngineering (R0)

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