Dense Motion Field and Uncovered Region Estimations for Low Bit-rate Video Coding Application

摘要

This paper presents a novel video-coding framework that uses dense motion field for efficient motion-compensated video coding. A new stochastic technique that is robust in overcoming the problem of occlusion is first used to estimate the dense motion field from the past-reconstructed frames. Using the continuum of motion in our proposed framework, the current dense motion field is predicted by projecting the estimated motion field. No motion information need to be coded since the decoder re-generates this motion information from its reconstructed frames. By making use of the predicted motion field, a novel uncovered background prediction is proposed to further improve the forward motion-compensated prediction. The algorithm is tested extensively on a number of standard video-conferencing sequences. With the same Peak Signal to Noise Ratio (PSNR) performance, an average compression gain of 17% is achieved as compared with the compression ratio of H.263 algorithm that uses the half-pel overlapped block-matching motion-compensated prediction.