随机抽样一致算法（RANdom SAmple Consensus,RANSAC）。它采用迭代的方式从一组包含离群的被观测数据中估算出数学模型的参数。 RANSAC是一个非确定性算法，在某种意义上说，它会产生一个在一定概率下合理的结果，而更多次的迭代会使这一概率增加。此RANSAC算法在1981年由Fischler和Bolles首次提出。

RANSAC的基本假设是

Random sample consensus (RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data which contains outliers. Therefore, it also can be interpreted as an outlier detection method. It is a non-deterministic algorithm in the sense that it produces a reasonable result only with a certain probability, with this probability increasing as more iterations are allowed. The algorithm was first published by Fischler and Bolles at SRI International in 1981.They used RANSAC to solve the Location Determination Problem (LDP), where the goal is to determine the points in the space that project onto an image into a set of landmarks with known locations.