The Role of detection Algorithm in Tracking Techniques with the help of Deep Learning for an Enhanced user Experience

Abstract

The drum set is a prominent instrument in a variety of music genres including pop, rock, and jazz. However, it costs money and space to get from nothing to purchasing a kit. The objective of these studies is to enable drummers to hone their skills, at least blithely, without a full set of drums and to expedite the initiation of drummers to their drumming experiences without incurring any costs. Drums do not fit inside a single bag, making them more difficult to travel than other instruments. We propose a virtual drum prototype that enables air-drumming using just two sticks, a computer equipped with a camera, and readily available markers that resemble the drumstick tips, such colourful papers. The detection algorithm combines tracking techniques with deep learning technology for an enhanced user experience. This was done using the Python-based OpenCV, as well as the concept of color-based blob recognition was used to find the markers. The capacity to function as a USB controller and MIDI controllers as well as the possibility for further development as a released program have all been shown by this prototype. Results from experiments show how useful and successful this method is for producing a lifelike and immersive virtual drumming experience.