A Camera Self-calibration Method Based on Hybrid Optimization Algorithm

摘要：

A new camera self-calibration approach is presented by combining an improved Genetic Algorithm (GA) with Levenberg-Marquardt (LM) algorithm. Firstly, the simplified Kruppa equation defined by Hartley is translated into the optimized cost function. Secondly, the minimum value of the optimized cost function is calculated by a hybrid optimization algorithm which combines the improved GA with LM algorithm. Finally, the intrinsic parameters of the camera are obtained. Several experiments are implemented to demonstrate the validity and the performance of the presented approach. The results show that it is accurate, and the accuracy of the proposed method is obviously improved compared with the single optimization methods.

关键词： self-calibration kruppa equations GA LM algorithm

作者: Li QiShen Lin LiCai Jiang ZeTao

作者单位: School of Computing Nanchang Hangkong University Nanchang, Jiangxi Province 330063, China

会议类型: 国际会议

会议名称: Second International Symposium on Electronic Commerce and Security(第二届电子商务与安全国际研究大会)(ISECS 2009)

会议地点: 南昌

会议语种:英文

页码: 716-720

在线出版日期: 2009-05-22（万方平台首次上网日期，不代表论文的发表时间）