We present a region of interest (ROI) based rate control for H.263 compatible video conferencing. A face detection and tracking scheme with very low complexity is proposed for segmentation. By analyzing quadratic rate models in frame layer, video object plane (VOP) layer, and macroblock (MB) layer extracted from the test data, a quadratic rate model at the MB layer with a modified physical meaning is proposed to improve the model accuracy. The basic idea is to use a group of uncoded MBs in the current VOP instead of individual MBs to update model parameters. A joint VOP layer and MB layer rate control algorithm is proposed. The VOP layer rate control assigns target bit rate for each VOP based on the coding complexity and visual importance, and determines an average quantization parameter (QP) for each VOP. Some new features of MB layer rate control are designed to utilize both average statistics of a VOP and individual statistics of MB together. The performance is compared with conventional TMN8 and object-based VM8 rate control, better peak SNR (PSNR) for ROI, and more accurate rate control can be achieved for various video sequences. The proposed rate control algorithm can be extended for H.264 ROI-based scalable video coding.