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Abstract : A system is presented for analysing drum performance video sequences. A novel ellipse detection algorithm is introduced that automatically locates drum tops. This algorithm fits ellipses to edge clusters, and ranks them according to various fitness criteria. A background/foreground segmentation method is then used to extract the silhouette of the drummer and drum sticks. Coupled with a motion intensity feature, this allows for the detection of 'hits' in each of the extracted regions. In order to obtain a transcription of the performance, each of these regions is automatically labeled with the corresponding instrument class. A partial audio transcription and color cues are used to measure the compatibility between a region and its label, the Kuhn-Munkres algorithm is then employed to find the optimal labeling. Experimental results demonstrate the ability of visual analysis to enhance the performance of an audio drum transcription system. Video processing Audio processing Multimodal processing Video stream Drum tops segmentation Hit detection Region to instrument mapping Audio transcription Audio stream Video transcription Audio/video fusion Audiovisual Transcription
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Contributor : Gaël RICHARD Connect in order to contact the contributor
Submitted on : Friday, February 26, 2021 - 7:02:18 PM
Last modification on : Tuesday, October 19, 2021 - 11:16:31 AM


  • HAL Id : hal-03153911, version 1



Kevin Mcguinness, Olivier Gillet, Noel E O'Connor, Gael Richard. VISUAL ANALYSIS FOR DRUM SEQUENCE TRANSCRIPTION. European Signal Processing Conference (Eusipco), 2007, Poznan, Poland. ⟨hal-03153911⟩



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