This article first discusses the two kinds of camera self-calibration algorithms: model-based camera self-calibration algorithm and fundamental matrix-based camera self-calibration algorithm.
首先讨论了两种摄像机自标定算法,即基于模型的摄像机自标定算法以及基于基础矩阵的摄像机自标定算法。
参考来源 - 两种多视图线性摄像机自标定算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
This paper analyzes the statistical characteristics of camera imaging error based on studying total least squares, and clarifies the error effect on estimating fundamental matrix.
在研究整体最小二乘法的基础上，分析摄像机成像误差的统计特征，明确误差对基础矩阵估计算法的影响。
The corner detection algorithm, avoidance of the degeneration problem and the fundamental matrix iterative optimization algorithm based on rank-2 constraint were introduced.
给出了角点检测算法、退化问题的避免措施以及基于秩2约束的基础矩阵迭代优化求解的方法。
To avoid sitting reference object on scene, the model of self-calibration based on fundamental matrix estimation and its implementation are proposed.
为避免测量过程中在现场设置标定参考点，研究了以基础矩阵估计为基础的交通事故摄影图像自标定模型，并分析了其实现过程。
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