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Trajectory estimation is a fundamental component of racket sport analytics,as the trajectory contains information not only about the winning and losing ofeach point, but also how it was won or lost. In sports such as badminton,players benefit from knowing the full 3D trajectory, as the height ofshuttlecock or ball provides valuable tactical information. Unfortunately, 3Dreconstruction is a notoriously hard problem, and standard trajectoryestimators can only track 2D pixel coordinates. In this work, we present thefirst complete end-to-end system for the extraction and segmentation of 3Dshuttle trajectories from monocular badminton videos. Our system integratesbadminton domain knowledge such as court dimension, shot placement, physicallaws of motion, along with vision-based features such as player poses andshuttle tracking. We find that significant engineering efforts and modelimprovements are needed to make the overall system robust, and as a by-productof our work, improve state-of-the-art results on court recognition, 2Dtrajectory estimation, and hit recognition.

MonoTrack: Shuttle trajectory reconstruction from monocular badminton video