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Landmark Dataset Development and Recognition

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  • Min Chen

    (University of Washington, Bothell, USA)

  • Hao Wu

    (University of Washington, Bothell, USA)

Abstract

Landmark recognition aims to detect popular natural and manmade structures within an image. It is challenging with one of the reasons being the lack of large annotated datasets. Existing work mainly focuses on landmarks located in Europe and North America due to regional and language bias. In this study, the authors build a comprehensive Chinese landmark dataset to complement the current data and to benefit research for landmark recognition. It is done by leveraging the vast amount of multimedia data on the web and utilizing image clustering and retrieval techniques in data preparation and analysis. This results in a Chinese landmark dataset with a total of 42,548 images for 987 unique landmarks. In addition, a landmark recognition model is developed based on advanced deep learning techniques and integrated into a mobile application that allows users to do landmark prediction without the need of internet access or cellular data coverage.

Suggested Citation

  • Min Chen & Hao Wu, 2021. "Landmark Dataset Development and Recognition," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 12(4), pages 38-51, October.
    • Handle: RePEc:igg:jmdem0:v:12:y:2021:i:4:p:38-51
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