摘要
针对大尺寸视觉测量中的高精度要求,提出了一种新的摄像机网络规划方法,结合实际视觉测量系统的各个环节,考虑了可见性、视场等多种约束对初始站位进行筛选,得到符合条件的有效站位,采用多细胞遗传算法在有效站位中搜索最优的摄像机站位组合。通过理论分析以及对抛物面天线的实验仿真,验证了该方法的有效性和准确性,研究内容对实际的视觉测量实验具有指导性作用。
A new method of camera planning is put forward to meet the need of high precision in large - scale vision measurement. Combined with each process in actual vision measurement, many constraints such as visibility and viewing field are considered to choose initial and valid camera placements. The combination of optimal placements of camera is searched in valid placements by using the multicellular genetic algorithm. The simulation results of experiment are proved to be veracity and efficiency of the solution. It will be of great guidance to actual experiments in vision measurement.
出处
《工具技术》
北大核心
2008年第2期64-67,共4页
Tool Engineering
基金
国家自然科学基金资助项目(项目编号:50475176
50675015)
北京市自然科学基金
北京市教委科技发展计划重点项目(项目编号:KZ200511232019)
北京市属市管高校人才强教计划资助项目(项目编号:PXM2007-014224-044674)
北京市教委科技发展计划面上项目(项目编号:KM200611232004)
关键词
视觉测量
站位约束
网络优化
遗传算法
vision measurement, placement constraint, network optimization, genetic algorithm