几何基元的提取方法

New method on extracting geometric primitives

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。

Extracting geometric primitives is very important in model\|based computer vision. This program can be treated as an optimum program, that is to find the optimum value of a cost function. The random sampling 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 order to reduce the cost of compute, increase the precision of the algorithm. The extraction algorithm can be used with multiple geometric primitives. \;