| 量子粒子群优化算法在摄像机标定中的应用 |
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| 引用本文： | 郁钱,孙俊,须文波.量子粒子群优化算法在摄像机标定中的应用[J].计算机工程与应用,2011,47(14):200-203. |
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| 作者姓名： | 郁钱 孙俊 须文波 |
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| 作者单位： | 江南大学信息工程学院,江苏无锡,214122 |
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| 摘 要： | 摄像机标定是三维重构中最关键的一步,它的精度直接决定了三维重构结果的逼真程度。为了能够提高摄像机标定的精度,克服传统优化算法易陷入局部最小,反投影误差大等缺点,首次将量子粒子群优化算法(Quantum-Behaved Particle Swarm Optimization,QPSO)应用于摄像机标定中。该方法利用传统的线性方法求得初始值,利用QPSO对初始值进行优化。实验数据表明,基于QPSO的摄像机标定的平均反投影误差小于一个像素,是一种可行的方法,且与智能优化算法PSO相比,基于QPSO的摄像机标定具有更小的误差。
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| 关 键 词： | 三维重构 最子粒子群优化算法(QPSO) 量子粒子群优化算法 摄像机标定 |
| 修稿时间： | |
Application of Quantum-Behaved Particle Swarm Optimization in camera calibration |
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| YU Qian,SUN Jun,XU Wenbo.Application of Quantum-Behaved Particle Swarm Optimization in camera calibration[J].Computer Engineering and Applications,2011,47(14):200-203. |
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| Authors: | YU Qian SUN Jun XU Wenbo |
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| Affiliation: | School of Information Engineering,Jiangnan University,Wuxi,Jiangsu 214122,China |
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| Abstract: | Camera calibration is a key step in three-dimensional reconstruction,which directly determines the accuracy of 3Dreconstruction.This paper firstly applies the Quantum-Behaved Particle Swarm Optimization to camera calibration in order toimprove the accuracy and overcome the drawbacks of traditional optimization algorithm,such as local-optima inclination andpoor back-projection error.Firstly,this method uses the traditional linear method to achieve the initial value,and then optimiz-es the initial value with QPSO.Experimental data show that camera calibration based on QPSO has less average back-projec-tion error than a pixel and is an effective and reliable method.Experiment also shows that this approach has lower errorthan the one based on PSO |
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| Keywords: | three-dimensional reconstruction Quantum-Behaved Particle Swarm Optimization （QPSO） Quantum-Behaved Particle Swarm Optimization camera calibration |
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