Author : Ms. Snehal Kshirsagar 1
Date of Publication :15th July 2017
Abstract: Music conduct by a group requires a conductor to play the music. These conductors perform various music patterns in front of band and depend on this pattern band play the music. The pattern or gesture perform by the conductor are require to be more precise and accurate to play the correct musical node. Because of this a conductor has to practice more and more to draw correct pattern. There is always requiring a teacher or a senior music moderator to judge wrong and right pattern drawn by beginner conductor. It is not always possible to observe each and every student whether they drawn correct or wrong pattern. To overcome this problem we proposed a new technique called Dynamic Time Warping for musical pattern detection. We have implemented this concept on basic three pattern detection. In this method we have used a camera to detect the hand movement and then apply DTW algorithm to detect the correct pattern drawn by the beginner conductor.
Reference :
-
- M. Mandanici and S. Sapir, “Disembodied voices: A Kinect virtual choir conductor,” in Proc. 9th Sound Music Comput. Conf., 2012, pp. 271–276.
- J.-S. Wang and F.-C. Chuang, “An accelerometerbased digital pen with a trajectory recognition algorithm for handwritten digit and gesture recognition,” IEEE Trans. Ind. Electron., vol. 59, no. 7, pp. 2998–3007, Jul. 2012.
- A Akl, C. Feng, and S. Valaee, “A novel accelerometer-based gesture recognition system,” IEEE Trans. Signal Process., vol. 59, no. 12, pp. 6197–6205, Dec. 2011.
- F. Zhou, F. D. la, and T. Frade, “Generalized time warping for multimodal alignment of human motion,” in Proc. IEEE Conf. Comput. Vis. Pattern Recog., Jun. 2012, pp. 1282 –1289 .
- S. Hussain and A. Rashid, “User independent hand gesture recognition by accelerated DTW,” in Proc. Int. Conf. Informat., Electron. Vis. 2012, pp. 1033–1037. [6] J. Wang, Z. Liu, Y. Wu, and J. Yuan, “Mining actionlet ensemble for action recognition with depth cameras,” in Proc. IEEE Conf. Comput. Vis. Pattern Recog., Jun. 2012, pp. 1290–1297.
- A.-L. Bianne-Bernard, F. Menasri, R.-H. Mohamad, C. Mokbel, C. Kermorvant, and L. Likforman-Sulem, “Dynamic and contextual information in HMM modeling for handwritten word recognition,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 10, pp. 2066–2080, Oct.2011.
- F. Bevilacqua, B. Zamborlin, A. Sypniewski, N.Schnell, F. Guédy, and N. Rasamimanana, “Continuous realtime gesture following and recognition,” in Proc. 8th Int. Conf. Gesture Embodied Commun. HumanComput. Interaction, 2010, pp. 73– 84.
- T. M. Nakra, Y. Ivanov, P. Smaragdis, and C. Ault, “The UBS virtual maestro: An interactive conducting system,” in Proc. Int. Conf. New Interfaces Musical Expression, 2009, pp. 250–255.
- L. Dahl, “Triggering sounds from discrete air gestures: What movement feature has the best timing?,” in Proc. Int. Conf. New Interfaces Musical Expression, London, U.K., Jun. 2014, pp. 201–206.
- L. Dahl, “Triggering sounds from discrete air gestures: What movement feature has the best timing?,” in Proc. Int. Conf. New Interfaces Musical Expression, London, U.K., Jun. 2014, pp. 201–206.
- aggelos pikrakis, sergios theodoridis, dimitris kamarotos,” recognition of isolated musical patterns using context dependent dynamic time warping”, ieee transactions on speech and audio processing, vol. 11, no. 3, may 2003