espiownage: Tracking Transients in Steelpan Drum Strikes Using Surveillance Technology
This work addresses the challenge of analyzing steelpan drum strikes for researchers in acoustics or materials science, but it is incremental as it builds on existing methods with dataset cleaning and updated libraries.
The researchers tackled the problem of tracking transient features in high-speed videos of steelpan drums using ESPI, achieving improvements of 10% or more on previous metric scores and introducing a segmentation-regression map for the entire drum surface.
We present an improvement in the ability to meaningfully track features in high speed videos of Caribbean steelpan drums illuminated by Electronic Speckle Pattern Interferometry (ESPI). This is achieved through the use of up-to-date computer vision libraries for object detection and image segmentation as well as a significant effort toward cleaning the dataset previously used to train systems for this application. Besides improvements on previous metric scores by 10% or more, noteworthy in this project are the introduction of a segmentation-regression map for the entire drum surface yielding interference fringe counts comparable to those obtained via object detection, as well as the accelerated workflow for coordinating the data-cleaning-and-model-training feedback loop for rapid iteration allowing this project to be conducted on a timescale of only 18 days.