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    Context based image analysis with application in dietary assessment and evaluation

    Access Status
    Fulltext not available
    Authors
    Wang, Y.
    He, Y.
    Boushey, Carol
    Zhu, F.
    Delp, E.
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Wang, Y. and He, Y. and Boushey, C. and Zhu, F. and Delp, E. 2017. Context based image analysis with application in dietary assessment and evaluation. Multimedia Tools and Applications. 77 (15): pp. 19769-19794.
    Source Title
    Multimedia Tools and Applications
    DOI
    10.1007/s11042-017-5346-x
    ISSN
    1380-7501
    School
    School of Public Health
    URI
    http://hdl.handle.net/20.500.11937/61568
    Collection
    • Curtin Research Publications
    Abstract

    Dietary assessment is essential for understanding the link between diet and health. We develop a context based image analysis system for dietary assessment to automatically segment, identify and quantify food items from images. In this paper, we describe image segmentation and object classification methods used in our system to detect and identify food items. We then use context information to refine the classification results. We define contextual dietary information as the data that is not directly produced by the visual appearance of an object in the image, but yields information about a user’s diet or can be used for diet planning. We integrate contextual dietary information that a user supplies to the system either explicitly or implicitly to correct potential misclassifications. We evaluate our models using food image datasets collected during dietary assessment studies from natural eating events.

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