该算法避开了烦琐的摄像机标定这一过程，也不用精确地求解单应性矩阵。
The algorithm avoid the cumbersome process of the camera calibration, and it does not accurately be solved single matrix.
论述由位于正交平面上的特征点对集合复原无穷远单应性矩阵和摄像机内参数的新算法。
A new algorithm is presented to determine infinite homography matrix and camera intrinsic matrix parameters under one camera motion set from the matched-point sets on two orthogonal planes.
首先，一个分段的双线性模型和5个5元的颜色编码的图像被用于构造的投影仪和一台摄像机的图像平面之间的单应性。
Firstly, a piecewise bilinear model and five 5-ary color coding images are used to construct the homography between the image planes of a projector and a camera.
利用单应矩阵的特性及近距离的双目一致性约束进行标定。
Characteristic homography matrix and consistency constraints in close range are employed in this calibration.
利用单应矩阵的特性及近距离的双目一致性约束进行标定。
Characteristic homography matrix and consistency constraints in close range are employed in this calibration.
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