Neuro-Calibration of a Camera using Particle Swarm Optimization

被引：0

作者：

Kumar, Sanjeev ^{[1
]}

Raman, Balasubramanian ^{[2
]}

Wu, Jonathan ^{[3
]}

机构：

[1] Univ Udine, Dept Maths & Comp Sci, Via Sci 206, I-33100 Udine, Italy

[2] IIT Roorkee, Dept Math, Uttarakhand 2476679, India

[3] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B3P4, Canada

来源：

2009 SECOND INTERNATIONAL CONFERENCE ON EMERGING TRENDS IN ENGINEERING AND TECHNOLOGY (ICETET 2009) | 2009年

关键词：

Camera Calibration; Gaussian Noise; Neural Network; Particle Swarm Optimization (PSO); Perspective Projection;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a particle swarm optimization (PSO) based camera calibration approach is presented to determine the external and internal calibration parameters from the knowledge of a given set of points in object space. First, the image formation model for a pinhole camera is formulated in terms of a feed-forward neural network (NN) and then this neural network is trained using particle swarm optimization. The effect of noise and number of control points are studied in the estimation of calibration parameters. Results from our extensive study are presented to demonstrate the excellent performance of the proposed technique in terms of convergence, accuracy, and robustness.

引用

页码：13 / +

页数：3

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