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Image Recognition-Based Tool for Food Recording and Analysis: FoodLog

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Connected Health in Smart Cities

Abstract

While maintaining a food record is an essential means of health management, there has long been a reliance on conventional methods, such as entering text into record sheets, in the health medicine field. Food recording is a time-consuming activity; hence, there is a need for innovation using information technology. We have developed the smartphone application “FoodLog,” as a new framework for food recording. This application uses digital pictures and is supported by image recognition and searches. It is available for general release. In this paper, we present an overview of this framework, the data statistics obtained using FoodLog, and the future prospects of this application.

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References

  1. K. Aizawa, M. Ogawa, FoodLog: Multimedia tool for healthcare applications. IEEE Multi Media 22(2), 4–9 (2015)

    Article  Google Scholar 

  2. FoodLog. http://app.foodlog.jp/

  3. K. Aizawa, K. Maeda, M. Ogawa, Y. Sato, M. Kasamatsu, K. Waki, H. Takimoto, Comparative study of the routine daily usability of FoodLog: A smartphone-based food recording tool assisted by image retrieval. J. Diabetes Sci. Technol. 8, 203–208 (2014)

    Article  Google Scholar 

  4. S. Amano, S. Horiguchi, K. Aizawa, K. Maeda, M. Kubota, M. Ogawa, Food search based on user feedback to assist image-based food recording systems, in ACM Multimedia Workshop on Multimedia Assisted Dietary Management (MADiMa), (2016), pp. 71–75

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  5. K. Waki, K. Aizawa, S. Kato, H. Fujita, H. Lee, H. Kobayashi, M. Ogawa, K. Mouri, T. Kadowaki, K. Ohe, DialBetics with a multimedia food recording tool, FoodLog: Smartphone-based self-management for type 2 diabetes. J. Diabetes Sci. Technol. 9(3), 534–540 (2015)

    Article  Google Scholar 

  6. GlucoNote. http://uhi.umin.jp/gluconote/ (2016)

  7. S. Amano, K. Aizawa, M. Ogawa, Food category representatives: Extracting categories from meal names in food recordings and recipe data, in IEEE International Conference on Multimedia Big Data, At Beijing, China, (2015), pp. 48–55

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  8. A. Tsubakida, S. Amano, K. Aizawa, M. Ogawa, Prediction of individual eating habits using short-term food recording, in International Joint Conference on Artificial Intelligence (IJCAI) Workshop CEA (2017), pp. 45–48

    Google Scholar 

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Correspondence to Kiyoharu Aizawa .

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Aizawa, K. (2020). Image Recognition-Based Tool for Food Recording and Analysis: FoodLog. In: El Saddik, A., Hossain, M., Kantarci, B. (eds) Connected Health in Smart Cities. Springer, Cham. https://doi.org/10.1007/978-3-030-27844-1_1

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  • DOI: https://doi.org/10.1007/978-3-030-27844-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27843-4

  • Online ISBN: 978-3-030-27844-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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