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Due to characteristics of human visual system (HVS), people usually focus more on a specific region named region-of-interest (ROI) of a video frame, rather than watch the whole frame. In addition, ROI-based video coding can also help to effectively reduce the number of encoding bitrates required for video transmission over networks, especially for the 3D-TV transmissions. Therefore, in this work, we propose a novel ROI-based bit allocation (BA) method which can adaptively extract and increase the visual quality of ROI while saving a huge number of encoding bitrates for video data. In the proposed method, we first detect and extract ROI based on the depth information obtained from 3D-TV video coding sequences. Then, based on the extracted ROI, a novel BA scheme is performed to solve the rate-distortion (R-D) optimization problem, in which the higher priority bitrates are adaptively assigned to ROI while the total encoding bitrates of video frames are kept satisfying all constraints required by the R-D optimization. Experimental results show that the proposed method provides much better higher peak signal-to-noise ratio (PSNR) as compared to other conventional BA methods.