Food is very essential for human life and it is fundamental to the human
experience. Food-related study may support multifarious applications and
services, such as guiding the human behavior, improving the human health and
understanding the culinary culture. With the rapid development of social
networks, mobile networks, and Internet of Things (IoT), people commonly
upload, share, and record food images, recipes, cooking videos, and food
diaries, leading to large-scale food data. Large-scale food data offers rich
knowledge about food and can help tackle many central issues of human society.
Therefore, it is time to group several disparate issues related to food
computing. Food computing acquires and analyzes heterogenous food data from
disparate sources for perception, recognition, retrieval, recommendation, and
monitoring of food. In food computing, computational approaches are applied to
address food related issues in medicine, biology, gastronomy and agronomy. Both
large-scale food data and recent breakthroughs in computer science are
transforming the way we analyze food data. Therefore, vast amounts of work has
been conducted in the food area, targeting different food-oriented tasks and
applications. However, there are very few systematic reviews, which shape this
area well and provide a comprehensive and in-depth summary of current efforts
or detail open problems in this area. In this paper, we formalize food
computing and present such a comprehensive overview of various emerging
concepts, methods, and tasks. We summarize key challenges and future directions
ahead for food computing. This is the first comprehensive survey that targets
the study of computing technology for the food area and also offers a
collection of research studies and technologies to benefit researchers and
practitioners working in different food-related fields.

该研究综述了食品计算的各种新兴概念、方法和任务，总结了面临的主要挑战和未来发展方向，并为从事不同食品相关领域的研究人员和实践者提供了一些研究研究和技术的收藏。