Affective music recommendation systembased on the mood of input video

Shoto Sasaki, Tatsunori Hirai, Hayato Ohya, Shigeo Morishima

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    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.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    PublisherSpringer Verlag
    Pages299-302
    Number of pages4
    Volume8936
    ISBN (Print)9783319144412
    Publication statusPublished - 2015
    Event21st International Conference on MultiMedia Modeling, MMM 2015 - Sydney, Australia
    Duration: 2015 Jan 52015 Jan 7

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume8936
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other21st International Conference on MultiMedia Modeling, MMM 2015
    CountryAustralia
    CitySydney
    Period15/1/515/1/7

    Fingerprint

    Mood
    Recommender systems
    Music
    Recommendations
    Recommendation System

    Keywords

    • Arousal
    • Image processing
    • Music recommendation
    • Valence

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

    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). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8936). Springer Verlag.

    Affective music recommendation systembased on the mood of input video. / Sasaki, Shoto; Hirai, Tatsunori; Ohya, Hayato; Morishima, Shigeo.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8936 Springer Verlag, 2015. p. 299-302 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8936).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    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, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8936, Springer Verlag, pp. 299-302, 21st International Conference on MultiMedia Modeling, MMM 2015, Sydney, Australia, 15/1/5.
    Sasaki S, Hirai T, Ohya H, Morishima S. 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. Springer Verlag. 2015. p. 299-302. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
    Sasaki, Shoto ; Hirai, Tatsunori ; Ohya, Hayato ; Morishima, Shigeo. / Affective music recommendation systembased on the mood of input video. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8936 Springer Verlag, 2015. pp. 299-302 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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