This paper proposes an aerodynamic analysis of the shuttlecock and a novel method for predicting shuttlecock trajectory. First, we have established a shuttlecock track data set by an infrared-based binocular vision system. Then the unscented Kalman filter algorithm is designed to further filter the noise and visual recognition algorithm errors. Third, the radial basis function (RBF)-based track prediction model is designed. This method offers a concept to obtain the neural network model of different kinds of flying or moving objects. The experimental results show that the proposed method can predict the shuttlecock trajectory in real time at high accuracy and can be used for implementing the algorithm of return strategies in the near future.

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In this paper, we describes a two dimensional(2D) color Grating Image system. Using digital image process technology, we get the information of every pixel of an color image, then, according to the relation of pixels and grating pattern, under the control of a computer, using laser light, we make tiny oriented diffraction grating on a recording plate. The result is brilliant kinetic image which is dazzling under any light source.

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