Abstract: A method and system for locating food items and determining their outlines in the images captured by a food preparation system is disclosed herein. The method relies on reliable annotated data to determine locations and outlines of food items, with a higher accuracy than conventional methods, due to the additional constraints provided by food item identities and cooking progress levels of the food items. With the location and outline determination performed prior to the cooking progress level determination in a separate process, the disclosed methods and systems allow for different types of foods to be cooked simultaneously and monitored individually, and improving the functions of the cooking appliances and the convenience of the users.

Abstract: A method and system for assessing individual and/or overall cooking progress of food items in a food preparation system is disclosed herein. The method for assessing cooking progress of food items relies on reliable annotated data in order to provide real-time feedback and guidance to a user. The methods and systems are specifically trained to optimize the accuracy of determining cooking progress of food items, utilizing a difference feature tensor that compares the cooking progress of a food item with a baseline image of the food item at the start of the cooking process. The noise and averaging effect due to the presence of different food items and/or same types of food items with slight variations in appearances and consistencies are reduced in the cooking progress level determination model, resulting in better accuracy of the cooking progress level assessment.

Abstract: The method and system disclosed herein presents a food preparation system that provides a user-friendly data collection and data annotation process that leverages crowd-sourced data to reduce the prohibitive costs associated with developing an extensive training set using dedicated cooking experiments and specialized manual annotation efforts. The food preparation system and corresponding method collect one or more data types (e.g., structured data such as temperature and weight data, and unstructured data such as images and thermal maps) and allow the collected data to be annotated by human users in order to provide information regarding the process of cooking, as well as food item identity, location, and/or outline information. A combination of image processing and user input is utilized in order to create models with food recognition and determining cooking progress.

Abstract: The method and system disclosed herein presents a food preparation system that provides a user-friendly data collection and data annotation process that leverages crowd-sourced data to reduce the prohibitive costs associated with developing an extensive training set using dedicated cooking experiments and specialized manual annotation efforts. The food preparation system and corresponding method collect one or more data types (e.g., structured data such as temperature and weight data, and unstructured data such as images and thermal maps) and allow the collected data to be annotated by human users in order to provide information regarding the process of cooking, as well as food item identity, location, and/or outline information. A combination of image processing and user input is utilized in order to create models with food recognition and determining cooking progress.