A significant improvement of block-based motion estimation strategies is presented, which supports fast computation and VLBR coding. For each block, a spatio-temporal context is defined based on nearest neighbors in the current and previous frames, and a prediction list is built. Then, the best matching vector within the list is chosen as an estimation of the block motion. An additional correction vector can be sent when the prediction error exceeds a threshold. Bit rate saving is achieved through an adaptive sorting of the prediction list of each block, which allows one to reduce the entropy of the motion indexes. Tests demonstrate a speed up above 1:200 as compared to full search, and a coding gain above 2, with a negligible loss of accuracy.