Abstract
We present an affective music recommendation system just fitting to an input video without textual information. Music that matches our current environmental mood can enhance a deep impression. However, we cannot know easily which music best matches our present mood from huge music database. So we often select a well-known popular song repeatedly in spite of the present mood. In this paper, we analyze the video sequence which represent current mood and recommend an appropriate music which affects the current mood. Our system matches an input video with music using valence-arousal plane which is an emotional plane.
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CITATION STYLE
Sasaki, S., Hirai, T., Ohya, H., & Morishima, S. (2015). Affective music recommendation systembased on the mood of input video. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8936, pp. 299–302). Springer Verlag. https://doi.org/10.1007/978-3-319-14442-9_33
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