Initialization of 3D human hand gesture is one of the fundamental and key steps in the study of 3D hand tracking, and a novel approach to initialize 3D human hand gesture is put forward in this paper. This paper will cover the following points. First, a new approach to selecting a human hand gesture from the hand postures database is presented. Second, both techniques of visualization and human- computer interaction are used into the initialization process, through which the 3D human hand model is finetuned time after time until the required accuracy is satisfied. Lastly, the proposed initialization method is applied to 3D human hand tracking system based on PF (Particle Filtering), with real video data under complex background. In order to address high dimensional problem of 3D hand structures, a new concept, which is called key factor in this paper, is introduced to guide sampling; to improve robustness to changing light conditions, a new skin model is proposed. The main contributions of this paper include: (1) combine the techniques of the interaction between operator and computer and the visualization to achieve initialization of 3D human hand model. (2) use the key factors to address the issue of high dimensionality of 3D hand model, and (3) a new hand skin model is presented, as well as self- occlusion problem is effective addressed. Our experimental results show that the proposed approach is not only fast, accurate and robust, but also direct, natural and convenient for operators to handle.