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Obesity treatment requires obese patients to record all food intakes per day. Computer vision has been introduced to estimate calories from food images. In order to increase accuracy of detection and reduce the error of volume estimation in…

Reliance on images for dietary assessment is an important strategy to accurately and conveniently monitor an individual's health, making it a vital mechanism in the prevention and care of chronic diseases and obesity. However, image-based…

Worldwide, in 2014, more than 1.9 billion adults, 18 years and older, were overweight. Of these, over 600 million were obese. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges…

Computer vision has been introduced to estimate calories from food images. But current food image data sets don't contain volume and mass records of foods, which leads to an incomplete calorie estimation. In this paper, we present a novel…

The increasing prevalence of diet-related chronic diseases coupled with the ineffectiveness of traditional diet management methods have resulted in a need for novel tools to accurately and automatically assess meals. Recently, computer…

Monitoring dietary intake is a crucial aspect of promoting healthy living. In recent years, advances in computer vision technology have facilitated dietary intake monitoring through the use of images and depth cameras. However, the current…

Image-based methods to analyze food images have alleviated the user burden and biases associated with traditional methods. However, accurate portion estimation remains a major challenge due to the loss of 3D information in the 2D…

Assessment of dietary intake has primarily relied on self-report instruments, which are prone to measurement errors. Dietary assessment methods have increasingly incorporated technological advances particularly mobile, image based…

Deep learning based methods have achieved impressive results in many applications for image-based diet assessment such as food classification and food portion size estimation. However, existing methods only focus on one task at a time,…

Dietary studies showed that dietary-related problem such as obesity is associated with other chronic diseases like hypertension, irregular blood sugar levels, and increased risk of heart attacks. The primary cause of these problems is poor…

We aim to estimate food portion size, a property that is strongly related to the presence of food object in 3D space, from single monocular images under real life setting. Specifically, we are interested in end-to-end estimation of food…

Accurate assessment of dietary intake requires improved tools to overcome limitations of current methods including user burden and measurement error. Emerging technologies such as image-based approaches using advanced machine learning…

Dietary assessment is essential to maintaining a healthy lifestyle. Automatic image-based dietary assessment is a growing field of research due to the increasing prevalence of image capturing devices (e.g. mobile phones). In this work, we…

In response to the increasing demand for efficient and non-invasive methods to estimate food weight, this paper presents a vision-based approach utilizing 2D images. The study employs a dataset of 2380 images comprising fourteen different…

Modern deep learning techniques have enabled advances in image-based dietary assessment such as food recognition and food portion size estimation. Valuable information on the types of foods and the amount consumed are crucial for prevention…

Accurate estimation of meal macronutrient composition is a pre-perquisite for precision nutrition, metabolic health monitoring, and glycemic management. Traditional dietary assessment methods, such as self-reported food logs or diet recalls…

Effective dietary monitoring is critical for managing Type 2 diabetes, yet accurately estimating caloric intake remains a major challenge. While continuous glucose monitors (CGMs) offer valuable physiological data, they often fall short in…

Calorie and nutrition research has attained increased interest in recent years. But, due to the complexity of the problem, literature in this area focuses on a limited subset of ingredients or dish types and simple convolutional neural…

Researches have shown that diet recording can help people increase awareness of food intake and improve nutrition management, and thereby maintain a healthier life. Recently, researchers have been working on smartphone-based diet recording…

In the process of intelligently segmenting foods in images using deep neural networks for diet management, data collection and labeling for network training are very important but labor-intensive tasks. In order to solve the difficulties of…