Anzeige
Erschienen in:
2015 | OriginalPaper | Buchkapitel
Affective Music Recommendation System Based on the Mood of Input Video
verfasst von : Shoto Sasaki, Tatsunori Hirai, Hayato Ohya, Shigeo Morishima
Erschienen in: MultiMedia Modeling
Verlag: Springer International Publishing
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.