Object Tracking with Monte Carlo Methods
基于蒙特卡罗方法的目标跟踪

For tracking object more robustly and rapidly, a novel approach for object tracking using Monte Carlo method is presented, which is motivated by the method of tracking with particle filter. In this approach, the locations and scales of the candidates in the next frame are sampled through Monte Carlo technique. Then the similitude degree between the samples and the reference objects are calculated. At last, the object states are estimated and the object under tracking is attained. This method does not need the motion information of the object, so it is especially good at tracking flexible object. The method is easier to implement than other present methods. Furthermore, it is proved to be quite robust and versatile by the numerical experiments.