ransac

In order to improve the speed of image registration , a fast method based on improved RANSAC algorithm is proposed .

为了提高图像配准的速度，提出了一种基于改进的随机抽样一致性（RANSAC）算法的快速图像配准方法。

To enhance the robustness of path parameter fitting , a least square method based on RANSAC is adopted .

拟合路径参数时引入RANSAC方法，以提高算法的可靠性；

Our algorithm gives better result than random sample consensus ( RANSAC ) algorithm with higher efficiency in the large nu .

大量实验结果表明，文中算法比随机抽样一致性算法的估计精度高，且计算效率高。

An improved RANSAC algorithm based on the modified median flow filter is presented to improve the stability and accuracy of homography calculation .

本文给出基于中值流滤波器的改进的RANSAC算法，保证了对应矩阵计算结果具有较高的精确性和稳定性。

At last , the points in image with the target point in calibration board were matched with the help of RANSAC random sampling algorithm .

然后用RANSAC随机采样算法对标定板上的点和图像上的点进行匹配。

We first fit the subspace to the detected trajectories robustly using RANSAC and then remove those that have large residuals .

我们第一次合适的子空间的轨迹鲁检测然后用RANSAC移除那些大型后遗症。

A linear equation is constructed from the local motion vector and the rigid model , and it determines the global motion parameters by the popular RANSAC algorithm .

通过局部运动矢量和刚体变换模型得到线性参数方程，并采用RANSAC算法进行求解，以获得全局运动参数。

Experimental results prove GCE has greater precision and robustness compared with RANSAC , MAPSAC , MLESAC and other robust algorithms .

仿真实验结果表明，相比于RANSAC、MAPSAC、MLESAC等鲁棒算法，该算法在估计精度和鲁棒性方面性能更优。

Use corner detection algorithm to get ear features , discuss the problem of using random sample consensus ( RANSAC ) algorithm to solve fundamental matrix for automatic ear feature matching .

通过检测角点获得耳朵特征点，讨论了采用随机采样一致性（RandomSampleConsensus，RANSAC）算法进行基础矩阵求解以自动匹配特征点时出现的问题。

In order to effectively eliminate the mismatched point pair , this algorithm based on SIFT often combined with Random Sample Consensus ( RANSAC ) algorithm to realize called " coarse + fine " matching model .

该配准算法往往结合随机抽样一致性（RANSAC）算法实现粗+精的匹配模式，有效剔除了误匹配点对。

Usually , camera self-calibration is nonlinear . A linear camera calibration technique based on four point correspondences is proposed in this paper in order to obtain a linear method , and a robust Euclidean reconstruction under the random sample consensus ( RANSAC ) algorithms is computed from the images .

摄像机自标定算法通常是非线性的，为了得到线性的方法，提出了一种在RANSAC框架下由4对图像对应点线性标定摄像机并对场景进行鲁棒性欧氏重建的方法。