AIxFood'21: 3rd workshop on AIxFood

• Main Authors: GUERRERO, Ricardo, SPRANGER, Michael, JIANG, Shuqiang, NGO, Chong-wah
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: computational food analysis; food; multimodal; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6629; https://ink.library.smu.edu.sg/context/sis_research/article/7632/viewcontent/3474085.3478573.pdf
• Institution: Singapore Management University

Food and cooking analysis present exciting research and application challenges for modern AI systems, particularly in the context of multimodal data such as images or video. A meal that appears in a food image is a product of a complex progression of cooking stages, often described in the accompanying textual recipe form. In the cooking process, individual ingredients change their physical properties, become combined with other food components, all to produce a final, yet highly variable, appearance of the meal. Recognizing food items or meals on a plate from images or videos, their physical properties such as the amount, nutritional content such as the caloric value, food attributes such as the flavor, elucidating the cooking process behind it, or creating robotic assistants that help users complete that cooking process, is of essential scientific and technological value yet technically extremely challenging. The 3rd AIxFood workshop was held as a half-day workshop in conjunction with the 29th ACM International Conference on Multimedia (ACM MM 2021), in Chengdu, China and virtually.