摘要
利用基于针孔相机模型的几何共线方程,建立像平面坐标和粒子三维空间坐标的映射关系,采用Tsai′s算法完成相机内外部参数标定,得到映射函数的解析式。基于像平面同名粒子是空间粒子在不同相机上的投影这一事实,提出一种较为简单的粒子匹配方法,在此基础上进行流场三维速度矢量重建方法研究和算法实现。标准图像仿真实验和氧化沟模型实验结果表明,该重建方法具有精度高、不需相机布局参数等特点,适合于与氧化沟模型类似流场的2D-3cPIV测量。
According to the geometrical collinear equation based on the pinhole camera model, this paper constructs the mapping relation between the image plane and three-dimensional physical space. The mapping function is determined by employing Tsai's algorithm to obtain the intrinsic and extrinsic parameters of the cameras. Based on the fact that the particles on different image planes are the projections from the same real particle on physical plane, the particle matching method is investigated in detail. Furthermore, the reconstruction method of three-dimensional velocity field is fully researched, which has the characteristic of high accuracy and does not require camera arrangement parameters. The investigated algorithm is successfully applied to the experiments of standard images and oxidation ditch model. Experimental results prove that the algorithm is suitable for the measurement of the flow fields such as oxidation ditch model.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2008年第6期1203-1208,共6页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(50778183)资助项目
关键词
PIV
共线方程
相机标定
三维速度重建
氧化沟模型
PIV collinear equation
camera calibration
3D velocity reconstruction
oxidation ditch model