Browse > Article
http://dx.doi.org/10.7471/ikeee.2019.23.1.249

Vision-Based Piano Music Transcription System  

Park, Sang-Uk (Dept. of Computer Education, SungKyunKwan University)
Park, Si-Hyun (Dept. of Computer Education, SungKyunKwan University)
Park, Chun-Su (Dept. of Computer Education, SungKyunKwan University)
Publication Information
Journal of IKEEE / v.23, no.1, 2019 , pp. 249-253 More about this Journal
Abstract
Most of music-transcription systems that have been commercialized operate based on audio information. However, these conventional systems have disadvantages of environmental dependency, equipment dependency, and time latency. This paper studied a vision-based music-transcription system that utilizes video information rather than audio information, which is a traditional method of music-transcription programs. Computer vision technology is widely used as a field for analyzing and applying information from equipment such as cameras. In this paper, we created a program to generate MIDI file which is electronic music notes by using smart-phone cameras to record the play of piano.
Keywords
Computer Vision; SVM; Music-transcription System; Smartphone Camera; Object Detection;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Broersen and Nijholt, "Developing a Virtual Piano Playing Environment," IEEE International conference, 2002.
2 Q Yang and G Essl, "Augmented Paino performance using a Depth Camera," NIME, 2012.
3 Aristotelis Handjakos, "Pianist Motion Capture with the Kinect Depth Camera," 2012.
4 A. Oka and M. Hashimoto, "Marker-Less Piano Fingering Recognition suing Sequential Depth Images," The 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision, pp. 1-4, 2013. DOI: 10.1109/FCV.2013.6485449
5 R. Bhuvaneswari and Ravi Subban, "Novel object detection and recognition system based on points of interest selection and SVM classification," ScienceDirect, Cognitive System Research 52, pp. 985-994, 2018. DOI: 10.1016/j.cogsys.2018.09.022   DOI
6 G. Mano, Y. Wu, M. Hor and C. Tang, "Real-Time Hand Detection and Tracking against Complex Background," Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 905-908, 2009. DOI: 10.1109/IIH-MSP.2009.133
7 Hemlata Chavan and Prateek Gupta, "A Review on Hand Gesture Detection Using Combine HSI, YCbCr and Morphological Method Recognition," International Research Journal of Engineering and Technology, vol. 03, no. 05, 2016.
8 Craig Stuart Sapp, "C++ library for parsing Standard MIDI Files," https://midifile.sapp.org.