基元提取在基于模型的计算机视觉中起着重要的作用。基元抽取问题可以归结为优化问题，即寻找代价函数的全局最小值。利用统计方法对最小子集进行随机抽样，大大减少了对最小子集的评价。同时引入了参数向量列表，并提出了一种新的代价函数，用于对基元的参数向量进行评价，使计算量减少、抽取精度提高。该方法可以用于多个基元的提取。分析实验结果表明，该方法能快速、准确地提取集合基元。

Extracting geometricprimitives is very important in model-based computer vision. This program can be treatedas an optimum program, that is to find the optimum value of a cost function. The randomsampling of minimal subsets with statistics can substantially reduce the cost of compute.The Parameter Vector List (PVL) and a new type robust cost function are presented in orderto reduce the cost of compute, increase the precision of the algorithm. The extractionalgorithm can be used with multiple geometric primitives.