Clustering Successive POCS for Fast Point Matching
用于快速特征点配准的聚类凸集投影算法

A clustering successive projection onto convex sets algorithm is presented for fast point matching.Via feature point clustering,the problem of matching two point sets is converted to that of matching corresponding clusters,which is then solved by a tailored successive projection onto covex sets(SPOCS) algorithm.The resulting algorithm can be viewed as an extention of SPOCS by combining with clustering.Its precision and computational complexity are decided by the clustering radius.Under the condition that the point sets' density is high,by choosing a proper radius,the computational burden can be reduced with only negligible deterioration of precision.Experimental results demonstrate the effectiveness of the algorithm.