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arXiv · 1812.03364

Engagement Estimation in Advertisement Videos with EEG

Sangeetha Balasubramanian·Shruti Shriya Gullapuram·Abhinav Shukla
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Abstract

Engagement is a vital metric in the advertising industry and its automatic estimation has huge commercial implications. This work presents a basic and simple framework for engagement estimation using EEG (electroencephalography) data specifically recorded while watching advertisement videos, and is meant to be a first step in a promising line of research. The system combines recent advances in low cost commercial Brain-Computer Interfaces with modeling user engagement in response to advertisement videos. We achieve an F1 score of nearly 0.7 for a binary classification of high and low values of self-reported engagement from multiple users. This study illustrates the possibility of seamless engagement measurement in the wild when interacting with media using a non invasive and readily available commercial EEG device. Performing engagement measurement via implicit tagging in this manner with a direct feedback from physiological signals, thus requiring no additional human effort, demonstrates a novel and potentially commercially relevant application in the area of advertisement video analysis.

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Sangeetha Balasubramanian, Shruti Shriya Gullapuram, Abhinav Shukla. 2018-12-08. Engagement Estimation in Advertisement Videos with EEG. https://arxiv.org/abs/1812.03364

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