An evaluation of a virtual atlas of portion sizes (VAPS) mobile augmented reality for portion size estimation.

Autor: Lam, Meng Chun, Suwadi, Nur Afyfah, Mohd Zainul Arifien, Adibah Huda, Poh, Bee Koon, Safii, Nik Shanita, Wong, Jyh Eiin
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Zdroj: Virtual Reality; Sep2021, Vol. 25 Issue 3, p695-707, 13p
Abstrakt: Food portion size estimation is a critical yet challenging task in dietary assessment. Augmented reality technology enables the presentation of food dimensions and volume in a virtual three-dimensional object. It has the potential to improve perception and estimation of portion sizes. This study aims to develop and evaluate a novel mobile augmented reality application, namely Virtual Atlas of Portion Sizes (VAPS), as a portion size estimation aid. The development methodology of VAPS involves food photography, reconstruction of 3D models using photogrammetry method and presenting them in an AR environment. The 3D food models displayed in either semi-transparent or vivid mode for users to perform food portion estimation. Users can then resize and rotate the 3D models to fit the virtual model with the actual food. A total of thirty-six participants were involved in the evaluation and were divided into a health science and a non-health science background group. VAPS received good usability level with 76 SUS score. In terms of task completion time, unsurprisingly, the health science group performed faster. However, both groups have equivalent accuracy on the food portion estimation task using VAPS: 22.5% for non-health science group and 26.6% for health science group. The health science group liked and have better accuracy in vivid 3D food models (37.5%). Meanwhile, the non-health science group preferred semi-transparent 3D food models, but the accuracy is not significantly different between semi-transparent (25%) and vivid 3D food model (20%). Results demonstrate the potential of VAPS to aid in portion size estimation for dietary assessment, and participants' feedback will be incorporated in the future for improvement of the app. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index