Trellis-based optimization of layer extraction for rate adaptation in real-time scalable stereo video coding

The concept of quality layers (QLs) has been adopted in the scalable video coding standard to enable optimal rate adaptation of precoded video in the rate-distortion sense. QLs were previously extended to stereo and multiple-view scalable video for efficient transport of 3DTV over the Internet. However, it is not possible to use the QL method in applications that require real-time encoding since the priority determination process assumes the availability of the whole video sequence. In this work, a trellis-based online rate adaptation is proposed for real-time scalable stereo video coding, with a delay of 1 group of pictures (GoP). The delay can be controlled by selection of the GoP size according to the application, such as 16 frames for live broadcast or 8 or 4 frames for videoconferencing. In addition, the joint optimization of layer extraction for scalable multiview coded stereo video is also proposed. It is assumed that the encoder/extractor is aware of the available dynamic network bandwidth in order to perform rate-distortion optimized medium-grain fidelity scalability layer selection for each GoP. Experimental results show that the performance of the proposed online method is very close to that of QLs that would require the whole video sequence.