Research of Tracking and Prediction of Moving Object with Kalman

Abstract

This paper puts forward a complete track forecasting models, using Kalman filter to track and predict the movement of objects without prior knowledge. Use the extracted Harris corner to calculate optical flow between two frames by L-K pyramid method, getting the convex hull of moving objects by optical flow clustering to separate the moving objects from background. Tracking and predicting the gravity of moving objects convex hull can solve the occlusion and separation problem between moving objects. Computer simulation and field test results show that the proposed method has higher tracking accuracy, and small amount of calculation.

Research on Image-Based Movement Accuracy Monitoring of Aerobics

“…It can be seen from Figure 4 that the proposed method has higher monitoring accuracy of calisthenic action trajectory than the methods proposed in reference [8][9], indicating that the proposed method can better improve the accuracy of monitoring of calisthenic action accuracy.…”

“…In order to prove the effectiveness of the image-based aerobics movement accuracy monitoring method proposed in this paper, taking Intel p42g processor as the hardware environment and Matlab2008a as the platform, the comparison method is used to compare the aerobics movement accuracy monitoring method proposed in this paper with those in references [8] and [9], and the experiment is completed.…”

“…en, the aerobic movement accuracy monitoring experiment was conducted and the accuracy of aerobic movement track monitoring was compared with the proposed method and reference [8][9]. e comparison results are shown in Figure 4.…”

“…However, the monitoring process of this method is complicated and thus time-consuming. For other literature, please refer to [4][5][6][7][8][9].…”