When and Why Static Images Are More Effective Than Videos

IEEE Transactions on Affective Computing(2023)

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摘要
People often prefer videos over images in research and applications, believing that videos are more effective for eliciting human emotions and building machine intelligence. However, our research shows that this assumption is not always correct when it comes to evoking emotions in human observers. In this article, we compare thirteen emotions and two perceptions elicited by short videos (2-6 second, silent video clips) versus static frames extracted from the videos. We show that static frames and videos elicit most emotions similarly, but static frames elicit negative emotions more strongly than videos. We test two complementary explanations: differential activation of suspense and the peak-end rule. These findings help us to computationally model human reactions more faithfully with fewer video frames. Our interdisciplinary results have important implications for methods, theory, and applications in diverse fields, including social psychology, computer vision, mass media, and marketing.
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关键词
Emotions,human psychophysics,video,frame,deep neural network
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