FoodChangeLens: CNN-based Food Transformation on HoloLens
Shu Naritmo Ryosuke Tanno Takumi Ege Keiji Yanai
Department of Informatics, The University of Electro-Communication
In Proc. of International Workshop on Interface and Experience Design with AI for VR/AR (DAIVAR 2018)
Demo Movie Version 1. It was created by Shu Naritomi and Takumi Ege.
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Demo Movie Version 2. It was created by Shu Naritomi and Takumi Ege.
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Abstract
In this demonstration, we implemented food category transformation in mixed reality using both image generation and HoloLens. Our system overlays transformed food images to food objects in the AR space, so that it is possible to convertin consideration of real shape. This system has the potential to make meals more enjoyable. In this work, we use the Conditional CycleGAN learned with a large-scale food image data collected from the Twitter Stream for food category transformation which can transform among ten kinds of foods mutually keeping the shape of a given food. We show the virtual meal experience that food category transformation among ten kinds of typical Japanese foods: ramen noodle, curry rice, fried rice, beef ricebowl, chilled noodle, spaghetti with meat source, white rice, eelbowl, and fried noodle.

Paper
PDF, 2018.
Citation
Shu Naritomi, Ryosuke Tanno, Takumi Ege, and Keiji Yanai. "FoodChangeLens:CNN-based Food Transformation on HoloLens", in Proc. of International Workshop on Interface and Experience Design with AI for VR/AR (DAIVAR), 2018. Bibtex
Another Application
Food Transfer Image Museum on HoloLensShu Naritomi made the above.
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Food Image-to-Image Translation using StarGANRyosuke Tanno made the above.
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Related Work
Acknowledgement
This work was supported by JSPS KAKENHI Grant Number 15H05915, 17H01745, 17H05972, 17H06026 and 17H06100.