Date of publication：2019-05-05 Number of clicks: 268
Congratulations! VIPL’ one survey paper “A Survey on Food Computing” is accepted by ACM Computing Surveys(CSUR). ACM CSUR is one of the most influential journals in computer science. This is the first CSUR paper in this lab!
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, such as guiding the human behavior, improving the human health and understanding the culinary culture. Therefore, it is time to group several disparate issues related to food computing. Food computing acquires and analyzes heterogenous food data from different sources for perception, recognition, retrieval, recommendation, and monitoring of food.
Both large-scale food data and recent breakthroughs in computer science are transforming the way we analyze food data. Therefore, a series of works have 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 proposed a food computing framework (As shown in Fig. 1) and present such a comprehensive overview of various emerging concepts, methods, and tasks. We also 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.
Fig. 1. An overview of food computing
Weiqing Min, Shuqiang Jiang*, Linhu Liu,Yong Rui and Ramesh Jain "A Survey on Food Computing," ACM Computing Surveys (CSUR) (Accepted on April 30,2019)