In order to eliminate the effect caused by noise

complex motion

and uncovered background in the process of real time segmenting video objects

a new method for real time segmenting video objects based on statistical change detection is proposed. During the process of statistical change detection

because t distribution is used to eliminate the effect of noise

the noise variance is not needed. Two frames at a distance of k are used for statistical change detection instead of two successive frames

thus articulation motion and slow motion can be better coped with. The intersection between two successive statistical change detection results can eliminate the effect of uncovered background

and most of the residual noise are eliminated at the same time without adding any computation complexity. The experimental results show that the new method solves the problems existing in the process of traditional statistical change detection caused by noise

complex motion

and uncovered background

and it can automatically segment video objects by real time. It can meet the requirements of many object based video applications such as MPEG-4.