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Face-to-face video teleconferencing is very important for real time communication. Current teleconferencing application uses stan-dard video codec, such as MPEG1/2/4, for the compression of face video. It either requires high bandwidth for high quality video transmission, or the transmitted face video be blurred at low bit-rate. In this paper, we present a system for real-time coding of face video at low bit-rate. There are two main contributions. First, we improve the technique of long term memory prediction by se-lecting frames into the database in an optimal way. A new frame is selected into the database only when it is significantly different from those frames which are already in the database. In this way, the database can cover a wider range of images. Second, we incor-porate the prior knowledge about faces into the long term memory prediction framework. The prior knowledge includes: (1) facial motions are repetitive such that most of them can be reconstructed from multiple reference frames; and (2) different components of the face and the background could tolerate different level of er-ror because of different perceptual importance. Experiments show that at similar PSNR the proposed system works much faster and achieves better visual quality than standard H.264/JVT codec. 1