A content-based bit allocation model for video streaming

Traditional video coding and streaming algorithms have not been fully utilized by using video content information for bit allocation and adaptation. This paper proposes a content-based video streaming method, based on a visual attention model to better utilize network bandwidth and achieve better subjective video quality. First, the visual attention model is exploited to segment the regions of interest (ROI) in video frames. Then, considering that the ROI is more sensitive to coding error than other regions, a region-weighted rate-distortion model is developed to allocate suitable bits for all ROI and non-ROI regions. The evaluation results indicate that more than 60% of the test video sequences encoded by the proposed method can obtain better subjective visual quality compared to the video encoded by classical methods under the same bandwidth, and about 20% of them can not be distinguished.