基于零空间投影和RQ分解的线性自标定

研究当模型矩阵已知时的摄像机自标定和目标三维重建。通过建立多视图目标深度矢量集合所在的零空间和目标模型矩阵的零空间之间的关系,应用零空间投影和RQ分解,开发从目标单视图或多视图同时完成摄像机自标定和目标三维重建的线性算法。实验演示了噪声强度、点数和帧数对算法性能的影响。理论分析和实验数据表明,该算法具有快速高效、简单实用、抗噪能力较强的优点。

Linear Algorithm of Camera Self-Calibration Based on Null Space Projection and RQ Decomposition

Camera self-calibration and 3D reconstruction, when model matrix is known, is studied. By building the relationship between the null space fell by the depth vector of the target imaged in the multi-view and the null space of the model shape matrix of the target, and by applying null space projection and RQ decomposition, a linear algorithm to simultaneously self-calibrate the camera and reconstruct the 3D pose or poses of the imaged target from single-view or multi-view. The affections of noise strength, point-number and frame-number on algorithm performance are experimentally demonstrated. The theoretical analysis and a great deal of the experiments have demonstrated that the suggested algorithm is fast, efficient, effect and rather robust to noise.