Presentation 2017-09-21
Feature Extraction and Impression Prediction of Presentation Slides
Shinji Oyama, Toshihiko Yamasaki, Kiyoharu Aizawa,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Presentation using slides is an effective way to deliver information in various fields. Although it has become easier to make slides due to the advancement of presentation software such as PowerPoint, it is still difficult for us to make slides easy to understand because few slide evaluation methods exist and we cannot objectively judge the impression of our slides. This paper experimentally shows that the style of slides affects the impression. And we predict the good-bad impression for a 1-page slide using proposed slide features. We also try a deep neural networks based method for impression prediction and analyze which parts of the slides affect the impression.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) slides / feature extraction / impression prediction
Paper # MVE2017-14
Date of Issue 2017-09-14 (MVE)

Conference Information
Committee MVE
Conference Date 2017/9/21(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Chiba Univ.
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Yoshinari Kameda(Univ. of Tsukuba)
Vice Chair Kenji Mase(Nagoya Univ.)
Secretary Kenji Mase(Kyoto Univ.)
Assistant Takatsugu Hirayama(Nagoya Univ.) / Ryosuke Aoki(NTT)

Paper Information
Registration To Technical Committee on Media Experience and Virtual Environment
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Feature Extraction and Impression Prediction of Presentation Slides
Sub Title (in English)
Keyword(1) slides
Keyword(2) feature extraction
Keyword(3) impression prediction
1st Author's Name Shinji Oyama
1st Author's Affiliation The University of Tokyo(Univ. of Tokyo)
2nd Author's Name Toshihiko Yamasaki
2nd Author's Affiliation The University of Tokyo(Univ. of Tokyo)
3rd Author's Name Kiyoharu Aizawa
3rd Author's Affiliation The University of Tokyo(Univ. of Tokyo)
Date 2017-09-21
Paper # MVE2017-14
Volume (vol) vol.117
Number (no) MVE-217
Page pp.pp.1-6(MVE),
#Pages 6
Date of Issue 2017-09-14 (MVE)