| Budget Amount *help |
¥18,850,000 (Direct Cost: ¥14,500,000、Indirect Cost: ¥4,350,000)
Fiscal Year 2019: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2018: ¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2017: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
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| Outline of Final Research Achievements |
In this study, we mainly studied the following five points to achieve highly accurate estimation of the amount of calories and nutrients in meals from photographs by using Web big data and deep learning. (1) Multi-task CNN-based calorie estimation for single-item meal images. (2) Individual meal calorie estimation for multiple meal images. (3) Realization of meal detection using region segmentation and rectangles, and creation of datasets for this purpose. (3) 3D meal shape estimation. We implemented 3D meal shape estimation for more accurate meal volume estimation. (4) High-Resolution food image translation using a large-scale Web food images and its application to food AR. (5) A new weakly-supervised region segmentation method is proposed and applied into food domain.
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