Impression Estimation of a Video Based on the Valence-Arousal Model

摘要

BGM (background music) of a video plays an important role for making a video impressive. Although a large number of royalty-free music clips are available on the web, it is still difficult for amateur video creators to select appropriate music clips for their videos. In this paper, we propose a computational method for estimating the impression of a video from auditory and visual features of a video. The impression of a video is modeled as the valence and arousal values. Based on the method, we propose a BGM recommendation system for supporting video creators. Experimental results have shown the effective of the impression estimation of a video based on the valence and arousal model.