Proceedings of the 18th Conference on Computer Science and Intelligence Systems

DOI: http://dx.doi.org/10.15439/2023F7106

Citation: Proceedings of the 18th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 35, pages 967–972 (2023)

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Abstract. The use of online video content plays a vital role in marketing strategies and is a significant component of internet usage. The challenge lies in evaluating the impact of video content on user engagement and finding ways to enhance its performance without employing techniques that overwhelm users or prompt ad avoidance behavior. This study investigates the correlation between video dynamics metrics and eye-tracking patterns to determine if user engagement, as indicated by fixations, is influenced by these metrics. The findings demonstrate that dynamic metrics can accurately predict eye-tracking patterns for brief videos and can be applied to measure both inter and intra-scene dynamics in multiscene videos.

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