用于特征点配准的快速聚类凸集投影算法

A CQPOCS Algorithm for Fast Feature Point Matching

提出一种用于特征点配准的快速聚类凸集投影算法．该算法首先将模板点集和目标点集的配准问题通过聚类转化为相应类集合的配准问题,降低了算法的计算量;进而采用基于二次规划的凸集投影来求解类配准问题,避免了序贯凸集投影算法由于交替行列投影而引起的积累误差．仿真表明,相对于现有的特征点配准算法,本文算法的配准精度和计算量均有所改善．

A clustering and quadratic programming based projection onto convex sets （CQPOCS） algorithm for fast feature point matching is presented in this paper. Via feature point clustering, the problem of matching model point set and taget point set is converted in to the problem of matching corresponding clusters, thus reducing the computational cost. Then, quatratic programming based POCS algorithm is used to solve the cluster matching problem without incurring the successive POCS algorithm＇s accumulating deviation due to successive projections onto row convex sets and column convex sets. Simulation results show that our CQPOCS algorithm has satisfactory matching accuracy and computational safety.