Abstract
The expansion of the home video market has created a requirement for video editing tools to allow ordinary people to assemble videos from short clips. However, professional skills are still necessary to create a music video, which requires a stream to be synchronized with pre-composed music. Because the music and the video are pre-generated in separate environments, even a professional producer usually requires a number of trials to obtain a satisfactory synchronization, which is something that most amateurs are unable to achieve.
Our aim is automatically to extract a sequence of clips from a video and assemble them to match a piece of music. Previous authors [8, 9, 16] have approached this problem by trying to synchronize passages of music with arbitrary frames in each video clip using predefined feature rules. However, each shot in a video is an artistic statement by the video-maker, and we want to retain the coherence of the video-maker’s intentions as far as possible.
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Notes
- 1.
http://visualcomputing.yonsei.ac.kr/personal/yoon/music.htm.
References
Avid Technology Inc (2007) User guide for pinnacle studio 11. Avid Technology Inc, Tewksbury
Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 8(6):679–698
Foote J, Cooper M, Girgensohn A (2002) Creating music videos using automatic media analysis. In: Proceedings of ACM multimedia. ACM, New York, pp 553–560
Gose E, Johnsonbaugh R, Jost S (1996) Pattern recognition and image analysis. Prentice Hall, Englewood Cliffs
Goto M (2001) An audio-based real-time beat tracking system for music with or without drum-sounds. J New Music Res 30(2):159–171
Helmholtz HL (1954) On the sensation of tone as a physiological basis for the theory of music. Dover (translation of original text 1877)
Hu M (1963) Visual pattern recognition by moment invariants. IRE Trans Inf Theo 8(2):179–187
Hua XS, Lu L, Zhang HJ (2003) Ave—automated home video editing. In: Proceedings of ACM multimedia. ACM, New York, pp 490–497
Hua XS, Lu L, Zhang HJ (2004) Automatic music video generation based on temporal pattern analysis. In: 12th ACM international conference on multimedia. ACM, New York, pp 472–475
Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254–1259
Jehan T, Lew M, Vaucelle C (2003) Cati dance: self-edited, self-synchronized music video. In: SIGGRAPH conference abstracts and applications. SIGGRAPH, Sydney, pp 27–31
Lan DJ, Ma YF, Zhang HJ (2003) A novel motion-based representation for video mining. In: Proceedings of the IEEE international conference on multimedia and expo. IEEE, Piscataway, pp 6–9
Lee HC, Lee IK (2005) Automatic synchronization of background music and motion in computer animation. In: Proceedings of eurographics 2005, Dublin, 29 August–2 September 2005, pp 353–362
Lucas B, Kanade T (1981) An iterative image registration technique with an application to stereo vision. In: Proceedings of 7th international joint conference on artificial intelligence (IJCAI), Vancouver, August 1981, pp 674–679
Ma YF, Zhang HJ (2003) Contrast-based image attention analysis by using fuzzy growing. In: Proceedings of the 11th ACM international conference on multimedia. ACM, New York, pp 374–381
Mulhem P, Kankanhalli M, Hasan H, Ji Y (2003) Pivot vector space approach for audio-video mixing. IEEE Multimed 10:28–40
Murat Tekalp A (1995) Digital video processing. Prentice Hall, Englewood Cliffs
Scheirer ED (1998) Tempo and beat analysis of acoustic musical signals. J Acoust Soc Am 103(1):588–601
Acknowledgements
This research is accomplished as the result of the promotion project for culture contents technology research center supported by Korea Culture & Content Agency (KOCCA).
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Yoon, JC., Lee, IK., Byun, S. (2009). Automated Music Video Generation Using Multi-level Feature-based Segmentation. In: Furht, B. (eds) Handbook of Multimedia for Digital Entertainment and Arts. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-89024-1_17
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