Skip to main content
SpringerLink
Log in

Affective Music Recommendation System Based on the Mood of Input Video

  • Conference paper
MultiMedia Modeling (MMM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8936))

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Russell, J.: A circumplex model of affect. Journal of Personality and Social Psychology 39(6), 1161–1178 (1980)

    Article  Google Scholar 

  2. Patricia, V., Albert, M.: Effects of color on emotions. Journal of Experimental Psychology: General 123(4), 394–409 (1994)

    Article  Google Scholar 

  3. Lang, P.J., Bradley, M.M., Cuthbert, B.N.: International aective picture system (IAPS): Aective ratings of pictures and instruction manual. Technical report A-6 University of Florida Gainesville (2008)

    Google Scholar 

  4. Eerola, T., Lartillot, O., Toiviainen, P.: Prediction of multidimension alemotional ratings in music from audio using multivariate regression models. In: Proceedings of the 10th International Conference on Music Information Retrieval, pp. 621–626 (2009)

    Google Scholar 

  5. Goto, M., Hashiguchi, H., Nishimura, T., Oka, R.: RWC music database: Music Genre Database and Musical Instrument Sound Database. In: Proceedings of the 4th International Conference on Music Information Retrieval, pp. 229–230 (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo, Japan, 169-8555

    Shoto Sasaki, Tatsunori Hirai & Hayato Ohya

  2. Waseda Research Institute for Science and Engineering, 3-4-1 Okubo, Shinjuku-ku, Tokyo, Japan, 169-8555

    Shigeo Morishima

Authors
  1. Shoto Sasaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tatsunori Hirai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hayato Ohya
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shigeo Morishima
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University of Technology, P.O. Box 123, 2007, Sydney, NSW, Australia

    Xiangjian He

  2. University of Newcastle, University Dr, Callaghan, 2308, NSW, Australia

    Suhuai Luo

  3. University of Technology, P.O. Box 123, 2007, Sydney, NSW, Australia

    Dacheng Tao  & Muhammad Abul Hasan  & 

  4. National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95, Zhongguancun East Road, 100190, Beijing, P.R. China

    Changsheng Xu

  5. Shanghai Jitotong University, 800 Dong Chuan Rd, 200240, Shanghai, China

    Jie Yang

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Sasaki, S., Hirai, T., Ohya, H., Morishima, S. (2015). Affective Music Recommendation System Based on the Mood of Input Video. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8936. Springer, Cham. https://doi.org/10.1007/978-3-319-14442-9_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14442-9_33

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14441-2

  • Online ISBN: 978-3-319-14442-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation