A Contextual Relation Networks for Mixed-Dish Recognition

25 May, 2020 by Jonathan Staniforth

Patent Name: A Contextual Relation Networks for Mixed-Dish Recognition

Filing No: 10201908103U (SG)

Filing Date: 9 May 2019

Country to be Filed: SG

Description: Mixed dish is a food category that contains different dishes mixed in one plate, and is popular in Eastern and Southeast Asia. Recognizing individual dishes in a mixed dish image is important for health related applications, e.g. calculating the nutrition values. However, most existing methods that focus on single dish classification are not applicable to mixed-dish recognition. The new challenge in recognizing mixed-dish images are the complex ingredient combination and severe overlap among different dishes. In order to tackle these problems, we propose a novel approach called contextual relation networks (CR-Nets) that encodes the implicit and explicit contextual relations among multiple dishes using region-level features and label-level co-occurrence, respectively. This is inspired by the intuition that people are likely to choose dishes with common eating habits, e.g., with multiple nutrition but without repeating ingredients. In addition, we collect a large-scale dataset of mixed dish images that contain 9, 254 mixed-dish images from 6 school canteens in Singapore. Extensive experiments on both our dataset and a smaller-scale public dataset validate that our CR-Nets can achieve top performance for localizing the dishes and recognizing their food categories

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