Automated music video generation using multi-level feature-based segmentation

We show how to create a music video automatically, using computable characteristics of the video and music to promote coherent matching. We analyze the flow of both music and video, and then segment them into sequences of near-uniform flow. We extract features from the both video and music segments, and then find matching pairs. The granularity of the matching process can be adapted by extending the segmentation process to several levels. Our approach drastically reduces the skill required to make simple music videos.

Siwoo ByunEmail:

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Jong-Chul Yoon   received his B.S. and M.S. degree in Media from Ajou University in 2003 and 2005, respectively. He is currently a Ph.D. candidate in the Computer Science from Yonsei University. His research interests include computer animation, multi-media control, and geometric modeling. In-Kwon Lee   received his B.S. degree in Computer Science from Yonsei University in 1989 and earned his M.S. and Ph.D. in Computer Science from POSTECH in 1992 and 1997, respectively. Currently, he is teaching and researching in the area of computer animation, geometric modeling, and computational music in Yonsei University. Siwoo Byun   received his B.S. degree in Computer Science from Yonsei University in 1989 and earned his M.S. and Ph.D. in Computer Science from Korea Advanced Institute of Science and Technology (KAIST) in 1991 and 1999, respectively. Currently, he is teaching and researching in the area of distributed database systems, mobile computing, and fault-tolerant systems in Anyang University.