Akinori Sato

Finished Master in AY2018

Main projects

Food attractiveness measurements

In this research, we analyze the attractiveness of food images using image analysis, including gaze information to improve the results.

Recent publications

Gaze-inspired Learning for Estimating the Attractiveness of a Food Photo

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
Proceedings of 20th IEEE Int. Symposium on Multimedia (ISM2018), pp.36-43, December 2018.

Gaze-inspired learning for estimating the attractiveness of a food photo

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
Proc. 20th IEEE Int. Symposium on Multimedia (ISM2018), December 2018.

Attractiveness estiamtionn method of food photos using gaze information (in Japanese)

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
IEICE SIG Attractiveness Computing Symposium 2018, September 2018.

Estimating the attractiveness of a food photo using a Convolutional Neural Network (in Japanese)

Akinori Sato, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase
IEICE Tech. Rep. Media Experience and Virtual Environment, October 2017.

Improvement of an attractiveness of food photos by using gaze information during preference experiment (in Japanese)

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
Proc. 2017 Electric / Electronic / Information Engineering Related Society Tokai Sectors Joint Convention, September 2017.

TBA (in Japanese)

Akinori Sato, Takatsugu Hirayama, Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase
IPSJ Tech. Rep. Computer Vision and Image Media, May 2017.

Contents Science Lab