Video codecs exploit temporal redundancy in video signals, through the use of motion compensated prediction, to achieve superior compression performance. The coding of motion vectors takes a large portion of the total rate cost. Prior research utilizes the spatial and temporal correlation of the motion field to improve the coding efficiency of the motion information. It typically constructs a candidate pool composed of a fixed number of reference motion vectors and allows the codec to select and reuse the one that best approximates the motion of the current block. This largely disconnects the entropy coding process from the block's motion information, and throws out any information related to motion consistency, leading to sub-optimal coding performance. An alternative motion vector referencing scheme is proposed in this work to fully accommodate the dynamic nature of the motion field. It adaptively extends or shortens the candidate list according to the actual number of available reference motion vectors. The associated probability model accounts for the likelihood that an individual motion vector candidate is used. A complementary motion vector candidate ranking system is also presented here. It is experimentally shown that the proposed scheme achieves about 1.6% compression performance gains on a wide range of test clips.
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