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Real Estate Image Analysis: A Literature Review

Author

Listed:
  • David Koch
  • Miroslav Despotovic
  • Sascha Leiber
  • Muntaha Sakeena
  • Mario Döller
  • Matthias Zeppelzauer

Abstract

Image analysis and computer vision are powerful techniques that are successfully used in different domains, but have hardly found their way into the real estate sector. However, real estate offers great potential, as there is a large amount of image content related to buildings and their surrounding implicitly providing rich building-related and contextual information. In the field of computer vision, there has recently been an increasing attention to real estate images. In this paper, we review current trends in real estate image analysis (REIA) and investigate the potential of image analysis for the real estate sector. We lay the groundwork for more comprehensive analyses of real estate image data, which should help to inspire novel approaches, methods, and services in the field.

Suggested Citation

  • David Koch & Miroslav Despotovic & Sascha Leiber & Muntaha Sakeena & Mario Döller & Matthias Zeppelzauer, 2019. "Real Estate Image Analysis: A Literature Review," Journal of Real Estate Literature, Taylor & Francis Journals, vol. 27(2), pages 269-300, December.
    • Handle: RePEc:taf:rjelxx:v:27:y:2019:i:2:p:269-300
    DOI: 10.22300/0927-7544.27.2.269
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    Cited by:

    1. Wan, Wayne Xinwei & Lindenthal, Thies, 2022. "Towards accountability in machine learning applications: A system-testing approach," ZEW Discussion Papers 22-001, ZEW - Leibniz Centre for European Economic Research.

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