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ObjectiveAccurate estimation of food portion size is of paramount importance in dietary studies. We have developed a small, chest-worn electronic device called eButton which automatically takes pictures of consumed foods for objective dietary assessment. From the acquired pictures, the food portion size can be calculated semi-automatically with the help of computer software. The aim of the present study is to evaluate the accuracy of the calculated food portion size (volumes) from eButton pictures.DesignParticipants wore an eButton during their lunch. The volume of food in each eButton picture was calculated using software. For comparison, three raters estimated the food volume by viewing the same picture. The actual volume was determined by physical measurement using seed displacement.SettingDining room and offices in a research laboratory.SubjectsSeven lab member volunteers.ResultsImages of 100 food samples (fifty Western and fifty Asian foods) were collected and each food volume was estimated from these images using software. The mean relative error between the estimated volume and the actual volume over all the samples was −2·8 % (95 % CI −6·8 %, 1·2 %) with sd of 20·4 %. For eighty-five samples, the food volumes determined by computer differed by no more than 30 % from the results of actual physical measurements. When the volume estimates by the computer and raters were compared, the computer estimates showed much less bias and variability.ConclusionsFrom the same eButton pictures, the computer-based method provides more objective and accurate estimates of food volume than the visual estimation method. [ABSTRACT FROM AUTHOR]

A novel method to estimate the 3D location of a circular feature from a 2D image is presented and applied to the problem of objective dietary assessment from images taken by a wearable device. Instead of using a common reference (e.g., a checkerboard card), we use a food container (e.g., a circular plate) as a necessary reference before the volumetric measurement. In this paper, we establish a mathematical model formulating the system involving a camera and a circular object in a 3D space and, based on this model, the food volume is calculated. Our experiments showed that, for 240 pictures of a variety of regular objects and food replicas, the relative error of the image-based volume estimation was less than 10% in 224 pictures.

Food portion size measurement combined with a database of calories and nutrients is important in the study of metabolic disorders such as obesity and diabetes. In this work, we present a convenient and accurate approach to the calculation of food volume by measuring several dimensions using a single 2-D image as the input. This approach does not require the conventional checkerboard based camera calibration since it is burdensome in practice. The only prior requirements of our approach are: 1) a circular container with a known size, such as a plate, a bowl or a cup, is present in the image, and 2) the picture is taken under a reasonable assumption that the camera is always held level with respect to its left and right sides and its lens is tilted down towards foods on the dining table. We show that, under these conditions, our approach provides a closed form solution to camera calibration, allowing convenient measurement of food portion size using digital pictures.

A wearable computer, called eButton, has been developed for evaluation of the human lifestyle. This ARM-based device acquires multimodal data from a camera module, a motion sensor, an orientation sensor, a light sensor and a GPS receiver. Its performance has been tested both in our laboratory and by human subjects in free-living conditions. Our results indicate that eButton can record real-world data reliably, providing a powerful tool for the evaluation of lifestyle for a broad range of applications.