NDLI: Particle-filter based audio-visual beat-tracking for music robot ensemble with human guitarist

Content Provider	IEEE Xplore Digital Library
Author	Itohara, T. Otsuka, T. Mizumoto, T. Ogata, T. Okuno, H.G.
Copyright Year	2011
Description	Author affiliation: Graduate School of Informatics, Kyoto University, Sakyo, 606-8501, Japan (Itohara, T.; Otsuka, T.; Mizumoto, T.; Ogata, T.; Okuno, H.G.)
Abstract	This paper presents an audio-visual beat-tracking method for ensemble robots with a human guitarist. Beat-tracking, or estimation of tempo and beat times of music, is critical to the high quality of musical ensemble performance. Since a human plays the guitar in out-beat in back beat and syncopation, the main problems of beat-tracking of a human's guitar playing are twofold: tempo changes and varying note lengths. Most conventional methods have not addressed human's guitar playing. Therefore, they lack the adaptation of either of the problems. To solve the problems simultaneously, our method uses not only audio but visual features. We extract audio features with Spectro-Temporal Pattern Matching (STPM) and visual features with optical flow, mean shift and Hough transform. Our beat-tracking estimates tempo and beat time using a particle filter; both acoustic feature of guitar sounds and visual features of arm motions are represented as particles. The particle is determined based on prior distribution of audio and visual features, respectively Experimental results confirm that our integrated audio-visual approach is robust against tempo changes and varying note lengths. In addition, they also show that estimation convergence rate depends only a little on the number of particles. The real-time factor is 0.88 when the number of particles is 200, and this shows out method works in real-time.
Starting Page	118
Ending Page	124
File Size	1809426
Page Count	7
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6094773
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Argon Noise Robots
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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