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.

在饮食评估中，食物份量的估算是一项至关重要但具有挑战性的任务。增强现实技术可以在虚拟三维对象中显示食物的尺寸和体积。它具有改善感知和估计尺寸的潜力。这项研究旨在开发和评估一种新颖的移动增强现实应用程序，即部分尺寸虚拟地图集（VAPS），作为部分尺寸估算的辅助工具。VAPS的开发方法包括食品摄影，使用摄影测量法重建3D模型并将其呈现在AR环境中。以半透明或生动模式显示的3D食物模型供用户执行食物份量估算。然后，用户可以调整3D模型的大小并旋转3D模型，以使虚拟模型与实际食物匹配。共有36位参与者参与了评估，并分为健康科学和非健康科学背景小组。VAPS以76 SUS得分获得了良好的可用性。就任务完成时间而言，毫无疑问，健康科学小组的执行速度更快。但是，两个组在使用VAPS进行食物份额估算任务中具有相同的准确性：非健康科学组为22.5％，健康科学组为26.6％。健康科学小组喜欢生动的3D食物模型，并且准确性更高（37.5％）。同时，非健康科学小组更喜欢半透明的3D食物模型，但半透明（25％）和生动的3D食物模型（20％）之间的准确性没有显着差异。结果表明VAPS有助于评估饮食评估的份量，