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《Computer Engineering》 2006-10
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Rectification of Magnetic Force Tracker in AR System

FENG Yan1, WANG Minghui2, CHEN Yimin1, HAN Jin1,3 (1. School of Computer Engineering and Science, Shanghai University, Shanghai 200072; 2. School of Mathematics and Science, Qufu Normal University, Qufu 273165; 3. Information Science and Engineering College, Shandong University of Science and Technology, Taian 271019)  
An approach using BP neural network is proposed to rectify the error. Considering that the neural network is prone to get local extremum and its convergence speed is slow, it utilizes the excellent global searching ability of genetic algorithm to optimize the initial weights and threshold of neural network. The results of experiment show that this method can not only improve the convergence precision of weights but also insure the neural network to get global convergence fleetly. After the tracker is rectified with the above method, the precision of AR system is improved prominently, consequently to enhance the third dimension of AR system.
【Fund】: 上海市自然科学基金资助项目(025115008)
【CateGory Index】: TP391.9
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【References】
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