In order to generate a three-dimensional virtual human animation with rich expression and smooth movement, a method for generating three-dimensional virtual human animation based on synchronous capture of facial expression and human pose with two cameras was proposed. Firstly, the Transmission Control Protocol (TCP) network timestamp method was used to realize the time synchronization of the two cameras, and the ZHANG Zhengyou's calibration method was used to realize the spatial synchronization of the two cameras. Then, the two cameras were used to collect facial expressions and human poses respectively. When collecting facial expressions, the 2D feature points of the image were extracted and the regression of these 2D points was used to calculate the Facial Action Coding System (FACS) facial action unit in order to prepare for the realization of expression animation. Based on the standard head 3D coordinate, according to the camera internal parameters, the Efficient Perspective- n-Point (EP nP) algorithm was used to realize the head pose estimation. After that, the facial expression information was matched with the head pose estimation information. When collecting human poses, the Occlusion-Robust Pose-Map (ORPM) method was used to calculate the human poses and output data such as the position and rotation angle of each bone point. Finally, the established 3D virtual human model was used to show the effect of data-driven animation in the Unreal Engine 4 (UE4). Experimental results show that this method can simultaneously capture facial expressions and human poses and has the frame rate reached 20 fps in the experimental test, so it can generate natural and realistic three-dimensional animation in real time.