Aiming at describing post probability distribution of the state with high dimensionality by using of a small amount of particles, a sampling in particle filtering for human hand 3D tracking is put forward in this paper. First of all, with the specific human-computer conditions, both cognitive psychology features of operators and motion features of the operators' hands are studied, upon which a novel concept, microstructure of state variable, is proposed. Then, a general method to describe the microstructure of state variable is further discussed. At last, a sampling algorithm based on the microstructure of state variable is put forward. The microstructure of state variable provide an unite and efficient mathematic model upon which the sampling algorithm may avoid sampling mass particles with poor quality. In order to validate validity and performance of sampling algorithm, a great deal of experiments are completed, and just fewer particles, compared with conventional particle filtering, may achieve better tracking precision.