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Human activity recognition is important in the study of personal health, wellness and lifestyle. In order to acquire human activity information from the personal space, many wearable multi-sensor devices have been developed. In this paper, a novel technique for automatic activity recognition based on multi-sensor data is presented. In order to utilize these data efficiently and overcome the big data...
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...
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...
Measuring food volume (portion size) is a critical component in both clinical and research dietary studies. With the wide availability of cell phones and other camera-ready mobile devices, food pictures can be taken, stored or transmitted easily to form an image based dietary record. Although this record enables a more accurate dietary recall, a digital image of food usually cannot be used to estimate...
In dietary studies, an accurate tool for diet assessment is highly required. In this paper, we present a new approach to the estimation of the food volume from a single input image based on the virtual reality (VR) technology. A virtual reality model is built for the estimation process and an algorithm is developed for the calculation of food volume. Experimental results have indicated high accuracy...
In order to understand the etiology of obesity related to people's diet, we have developed a method to calculate food volume (portion size) from a single digital image in which a dining plate was used as a reference. In order to evaluate the error of this method, we observe the relationship between the relative error under different food imaging scenarios, such as angles of camera rotation and distances...
This paper introduces the design and realization of a wearable device for dietary and physical activity monitoring. This design is based on technological advances in microelectronics and our previous prototypes which have verified the system concept. From our results, it is shown that the device meets all functional requirements as well as size and power consumption constraints essential to participants'...
Accurate estimation of food volume plays an important role in dietary assessment using digital photographs. In this paper, we present a new approach based on a circular object (e.g., a dining plate or a coin) as a physical reference to determine food portion size. A geometrical model relating the circular object and its image is built. An algorithm to estimate food volume using the geometric model...
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