A Transformer Based Cycle Posture Detection System Using 3D Pose Estimation Algorithm

The concept of “form recognition” has had a lot of applications from different times, such as art, training sports, and movement analysis. Nonetheless, bicycle configuration recognition is one of the areas that led to the development of a model that only earlier didn't receive much attention up to recently. The posture of cycling is also crucial for human health, in order to better analyze and correct posture, in our study, we present a bike form detection model which is a product designed for the use of leisure cyclists. Cyclists will be able to utilize this model to inspect whether they have a good sitting position, affect their acceleration, and improve their own well-being. We can now evaluate the position of joints and develop a system of grades with just a phone camera being used yet still achieving top level accuracy. In addition, our 3D pose estimation has been brought to cycling through our unique database that has shown remarkable results in terms of rider's posture improvement.