Evaluation Method for Video Advertisetments Using EEG Signals

Angello Dushantha, Rukshan Akalanka, Hemantha Gayan, Kasun C. Siriwardhana, P. Haddela, L. Wickramasinghe
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引用次数: 2

Abstract

Video advertisements became very popular in recent past due to the technology advancement and competitiveness of businesses. Therefore, analyzing the impact of commercial video advertisements are important before they launch the marketing campaign. This paper presents a unique method that can evaluate the effectiveness of movie commercials (trailers) using Electroencephalogram (EEG) signals captured from a brain computer interface. Randomly selected fifteen movie lovers were participated to capture EEG signals. For a selected set of movie trailers, three different type of classification models were trained and tested. With the help of classification models, it measures attention and enjoyment levels and also emotion status of a viewer to compute effectiveness of an advertisement. It also consists of a recommender system which suggests movie advertisements based on the preferences of the users. From the initial results received, it confirms that proposed framework is producing promising results. Even though this work focuses on the movie/entertainment industry, it has the potential to be developed and applied for many other industries as well.
基于脑电信号的视频广告评价方法
由于技术的进步和企业的竞争力,视频广告在最近变得非常流行。因此,在商业视频广告开展营销活动之前,分析其影响是非常重要的。本文提出了一种独特的方法,利用脑机接口捕获的脑电图(EEG)信号来评估电影广告(预告片)的有效性。随机选择15名电影爱好者参与捕捉脑电图信号。对于一组选定的电影预告片,我们训练并测试了三种不同类型的分类模型。在分类模型的帮助下,它测量观众的注意力和享受水平以及情感状态,以计算广告的有效性。它还包括一个推荐系统,根据用户的偏好推荐电影广告。从收到的初步结果来看,它证实拟议的框架正在产生有希望的结果。尽管这项工作主要集中在电影/娱乐行业,但它也有潜力被开发和应用于许多其他行业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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