Please use this identifier to cite or link to this item: https://doi.org/10.1145/1142020.1142023
Title: Automatic summarization of music videos
Authors: Shao, X.
Xu, C.
Maddage, N.C.
Tian, Q.
Kankanhalli, M.S. 
Jin, J.S.
Keywords: Music summarization
Music video
Video summarization
Issue Date: 2006
Source: Shao, X., Xu, C., Maddage, N.C., Tian, Q., Kankanhalli, M.S., Jin, J.S. (2006). Automatic summarization of music videos. ACM Transactions on Multimedia Computing, Communications and Applications 2 (2) : 127-148. ScholarBank@NUS Repository. https://doi.org/10.1145/1142020.1142023
Abstract: In this article, we propose a novel approach for automatic music video summarization. The proposed summarization scheme is different from the current methods used for video summarization. The music video is separated into the music track and video track. For the music track, a music summary is created by analyzing the music content using music features, an adaptive clustering algorithm, and music domain knowledge. Then, shots in the video track are detected and clustered. Finally, the music video summary is created by aligning the music summary and clustered video shots. Subjective studies by experienced users have been conducted to evaluate the quality of music summaries and effectiveness of the proposed summarization approach. Experiments are performed on different genres of music videos and comparisons are made with the summaries generated based on music track, video track, and manually. The evaluation results indicate that summaries generated using the proposed method are effective in helping realize users' expectations. © 2006 ACM.
Source Title: ACM Transactions on Multimedia Computing, Communications and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/39506
ISSN: 15516857
DOI: 10.1145/1142020.1142023
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