Network-adaptive low-latency video communication over best-effort networks

The quality of service limitation of today's best-effort networks poses major challenge for low-latency video communication. To combat network losses for real-time and on-demand video communication, which exhibits stronger dependency across packets, a network-adaptive coding scheme is employed to dynamically manage the packet dependency using optimal reference picture selection. The selection of the reference is achieved within a rate-distortion optimization framework and is adapted to the varying network conditions. For network-adaptive streaming of prestored video, based on an accurate loss-distortion model, a prescient scheme that optimizes the dependency of a group of packets is proposed to achieve global optimality as well as improved rate-distortion performance. With the improved trade-off between compression efficiency and error resilience, the proposed system does not require retransmission of lost packets, which makes less than one-second low-latency communication possible.