In the current age of expanding access to the Internet, there has
been a flood of videos on the web. Studying the human cognitive
factors that affect the consumption of these videos is becoming
increasingly important, to be able to effectively organize and curate
them. One such important cognitive factor is Video Memorability,
which is the ability to recall a video’s content after watching it.
In this paper, we present our approach to solving the MediaEval
2018 Predicting Media Memorability Task. We develop a 3-forked
pipeline for predicting Memorability Scores, which leverages the
visual image features (both low-level and high-level), the image
saliency in different video frames, and the information present in
the captions. We also explore the relevance of other features such
as image memorability scores of the different frames in the video,
and present a detailed analysis of the results.