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    The use of co-occurrence patterns in single image based food portion estimation

    Access Status
    Fulltext not available
    Authors
    Fang, S.
    Zhu, F.
    Boushey, Carol
    Delp, E.
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Fang, S. and Zhu, F. and Boushey, C. and Delp, E. 2018. The use of co-occurrence patterns in single image based food portion estimation, pp. 462-466.
    Source Title
    2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
    DOI
    10.1109/GlobalSIP.2017.8308685
    ISBN
    9781509059904
    School
    School of Public Health
    URI
    http://hdl.handle.net/20.500.11937/68941
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 IEEE. Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. Food portions estimation is a challenging problem as food preparation and consumption process pose large variations on food shapes and appearances. We use geometric model based technique to estimate food portions and further improve estimation accuracy using co-occurrence patterns. We estimate the food portion co-occurrence patterns from food images we collected from dietary studies using the mobile Food Record (mFR) system we developed. Co-occurrence patterns is used as prior knowledge to refine portion estimation results. We show that the portion estimation accuracy has been improved when in-corporating the co-occurrence patterns as contextual information.

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