Table Tennis Capture System Based on Image Recognition and Modeling

This article takes table tennis as the research object, mainly extracts a large number of table tennis video trajectories, and combines the kinematic analysis method to reduce the noise of the extracted target to improve the accuracy of the table tennis trajectory and obtain the table tennis trajectory. The parameter group is used to simulate the trajectory of table tennis; based on the MATLAB environment to realize the table tennis trajectory simulation that provides the initial velocity and coordinates, complete the capture of the table tennis drop point. This article uses the two-dimensional information in the image to estimate the parameter values that form the three-dimensional information and then calculates the three-dimensional information based on the estimated parameter values. The unscented Kalman filter is used to estimate the trajectory parameters and rotation parameters of table tennis, and the algorithm for calculating and updating markers in real time is proposed, which reduces the influence of calculation errors on the estimation process and improves the accuracy of parameter estimation. First, establish a table tennis movement model and choose a suitable model to describe the translation and rotation movement of the table tennis. Then, based on the extended Kalman filter algorithm and the unscented Kalman filter algorithm, the ball flight trajectory estimation algorithm is established. Finally, an actual image acquisition system is built to collect trajectory information and surface information images from the actual table tennis movement. Processing is performed to obtain the positions of the center of the ping pong ball and the marked points on the corresponding sensors. Simulation and experimental results show that the proposed algorithm can effectively estimate the trajectory, linear velocity, and angular velocity parameters of a table tennis ball, and the selection of the initial value has little effect on the algorithm.