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| 基于平行性约束的摄像机标定与3D重构 |
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段福庆1, 吴福朝2, 胡占义2
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1.北京师范大学,信息科学与技术学院,北京,100875;2.中国科学院,自动化研究所,模式识别国家重点实验室,北京,100080
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| 摘要: |
| 引入了梯形的一个仿射不变量,并利用这个不变量,建立了梯形的相似不变量与摄像机内参数之间的约束关系.基于这个约束关系,利用摄像机内参数的知识或梯形相似不变量的知识,可以线性确定摄像机的内参数、运动参数和梯形的相似不变量.由于梯形是由一对平行线段唯一确定的,平行线段在许多场景中经常出现,因而该方法有很广泛的适用性.实验结果表明了该算法的有效性.该工作提供了一个基于平行性约束的框架,以往的基于平行四边形、平行六面体的方法都可以纳入到这个框架中. |
| 关键词: 不变量 平行性约束 摄像机标定 3D重构 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60575019, 60673100 (国家自然科学基金) |
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| Camera Calibration and 3D Reconstruction Using Parallelism Constraint |
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DUAN Fu-Qing,WU Fu-Chao,HU Zhan-Yi
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| Abstract: |
| This paper introduces an affine invariant of trapezia, and the explicit constraint equation between the intrinsic matrix of a camera and the similarity invariants of a trapezium are established using the affine invariant. By this constraint, the inner parameters, motion parameters of the cameras and the similarity invariants of trapezia can be linearly determined using some prior knowledge on the cameras or the trapezia. The proposed algorithms have wide applicability since parallel lines are not rare in many scenes. Experimental results validate the proposed approaches. This work presents a unifying framework based on the parallelism constraint, and the previous methods based on the parallelograms or the parallelepipeds can be integrated into this framework. |
| Key words: invariant parallelism constraint camera calibration 3D reconstruction |
