著者

Kenta Masui Genki Okada Norimichi Tsumura

出版者

The Institute of Image Information and Television Engineers

雑誌

ITE Transactions on Media Technology and Applications (ISSN:21867364)

巻号頁・発行日

vol.8, no.1, pp.49-59, 2020 (Released:2020-01-01)

参考文献数

35

被引用文献数

10

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The market size of online video advertising is expanding rapidly along with the spread of smartphones and social media. In this study, we estimate advertising effectiveness in the natural environment using online data collection and the remote measurement of webcam facial expressions and physiological responses. We collected 4, 108 videos of the faces of 411 Japanese people who were watching the video advertisement in their natural environment via the Internet. Facial expression and physiological responses such as heart rate and gaze were remotely measured by analyzing facial videos. We found that the accuracies of ad liking and purchase intent prediction are better when various acquired features are combined and machine learning is used than when only single-mode features are used. In addition, we aim to improve prediction accuracy by clustering the personality of the subjects and designing an estimation model for each personality.

著者

Wei-Ta Chu Hideto Motomura Norimichi Tsumura Toshihiko Yamasaki

出版者

The Institute of Image Information and Television Engineers

雑誌

ITE Transactions on Media Technology and Applications (ISSN:21867364)

巻号頁・発行日

vol.7, no.2, pp.60-67, 2019 (Released:2019-04-01)

参考文献数

72

被引用文献数

3

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With the advances in digital media processing technologies and the tremendous growth in the amount of digital media that have been created, new artworks are becoming possible and drawing much attention from researchers, industry, and consumers. A related emerging research area is the evaluation of such multimedia artworks by machine learning techniques. We call this research area “attractiveness computing.” Attractiveness computing is made possible by the great accumulation of such multimedia artworks and of consumers' responses. In this paper, we review existing research on multimedia artworks analysis and attractiveness computing.