Advancements in Machine Learning and Computer Vision Approaches for Food and Nutrient Recognition from Images: A Survey

Along with physical activity and exercise, maintaining a nutritious diet is crucial to preventing obesity and a number of illnesses like diabetes, stroke, and cardiovascular diseases. The development of solutions for the automatic monitoring of dietary intake has been made possible by recent advancements in machine learning applications for computer vision. They contribute in providing a seamless approach to track daily food consumption and regulate eating patterns with improved precision as compared to conventional systems which rely mainly on manual input. This survey examines modern vision-based algorithms based on machine learning used in autonomous dietary evaluation and presents their performance, usability as well as the limitations and obstacles which are yet to be solved.