A2D: Anywhere Anytime Drumming
April 04, 2023 Β· Declared Dead Β· π 2023 IEEE Region 10 Symposium (TENSYMP)
"No code URL or promise found in abstract"
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Authors
Harel Yadid, Almog Algranti, Mark Levin, Ayal Taitler
arXiv ID
2304.03289
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.SD,
eess.AS
Citations
4
Venue
2023 IEEE Region 10 Symposium (TENSYMP)
Last Checked
4 months ago
Abstract
The drum kit, which has only been around for around 100 years, is a popular instrument in many music genres such as pop, rock, and jazz. However, the road to owning a kit is expensive, both financially and space-wise. Also, drums are more difficult to move around compared to other instruments, as they do not fit into a single bag. We propose a no-drums approach that uses only two sticks and a smartphone or a webcam to provide an air-drumming experience. The detection algorithm combines deep learning tools with tracking methods for an enhanced user experience. Based on both quantitative and qualitative testing with humans-in-the-loop, we show that our system has zero misses for beginner level play and negligible misses for advanced level play. Additionally, our limited human trials suggest potential directions for future research.
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