Abstract
The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera [e.g. Apple iPhone, Apple iPod Touch (Apple Inc., Cupertino, CA, USA); Nexus One (Google, Mountain View, CA, USA)]. Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis (i.e. segmentation, feature extraction and classification), which allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies to provide a detailed diet analysis for use in epidemiological or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarises the system design and the evidence-based development of image-based methods for dietary assessment among children.
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