Gathering pattern is an important research topic in the field of trajectory pattern mining. It focus on collective gathering problem on consecutive time period. Traditional models of gathering patterns are based on co-concurrence patterns. Mining methods based on such models generate a lot of stationary gathering groups. In order to deal with such problems, we propose a converging pattern based on modelling of group moving objects, which accurately identifies gathering group instead of other types of moving group. A moving objects converging pattern mining (CPM) algorithm is presented and implemented. First, the algorithm locates all high density peak points and converges central zones. Second, the algorithm identifies converging groups on consecutive timestamps, and then detects converging patterns according to the durability of group patterns. Experimental results show the effectiveness and efficiency of the algorithm.