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Interior Design Network of Furnishing and Color Pairing with Object Detection and Color Analysis Based on Deep Learning

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Computer-Aided Architectural Design. Design Imperatives: The Future is Now (CAAD Futures 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1465))

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Abstract

Furnishing is one of the most important interior design elements when decorating a space. Because every interior design element is colored, it is essential to consider the pairing of furnishing and color during the design process. Despite the importance of the furnishing and color pairing, the decision-making process by which the pairings are made remains a “black-box” of the interior design process. However, the advancement of social networks and online interior-design platforms such as Today’s House allows collecting large quantities of actual interior design cases that can be shared publicly. In addition, it has become possible to extract various features and relationships of data through machine learning techniques and network analysis. Thus, this paper proposes a data-driven approach to reveal distinct patterns of furnishing and color pairing through object detection, color extraction, and network analysis. To do that, we collected a large quantity of image data (N = 14,111) from Today’s House (ohou.se) online interior-design platform. Then, we extracted furnishing objects and color palettes from the collected images using object detection and color extraction algorithms. Finally, we identified distinctive patterns of furnishing and color pairing through network analysis.

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Acknowledgements

This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP: Ministry of Science, ICT and Future Planning) (NRF-2020R1C1C1011974).

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Authors and Affiliations

  1. Department of Interior Architecture Design, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul, Korea

    Bo Hyeon Park, Kihoon Son & Kyung Hoon Hyun

Authors
  1. Bo Hyeon Park
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  2. Kihoon Son
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  3. Kyung Hoon Hyun
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Corresponding author

Correspondence to Kyung Hoon Hyun .

Editor information

Editors and Affiliations

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

    David Gerber

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

    Evangelos Pantazis

  3. Florida International University, Miami, FL, USA

    Biayna Bogosian

  4. University of Calgary, Calgary, Canada

    Alicia Nahmad

  5. Aalto University, Espoo, Finland

    Constantinos Miltiadis

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Park, B.H., Son, K., Hyun, K.H. (2022). Interior Design Network of Furnishing and Color Pairing with Object Detection and Color Analysis Based on Deep Learning. In: Gerber, D., Pantazis, E., Bogosian, B., Nahmad, A., Miltiadis, C. (eds) Computer-Aided Architectural Design. Design Imperatives: The Future is Now. CAAD Futures 2021. Communications in Computer and Information Science, vol 1465. Springer, Singapore. https://doi.org/10.1007/978-981-19-1280-1_15

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  • DOI: https://doi.org/10.1007/978-981-19-1280-1_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1279-5

  • Online ISBN: 978-981-19-1280-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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