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In this paper, we study a simplified affine motion model based codingframework to overcome the limitation of translational motion model and maintainlow computational complexity. The proposed framework mainly has three keycontributions. First, we propose to reduce the number of affine motionparameters from 6 to 4. The proposed four-parameter affine motion model can notonly handle most of the complex motions in natural videos but also save thebits for two parameters. Second, to efficiently encode the affine motionparameters, we propose two motion prediction modes, i.e., advanced affinemotion vector prediction combined with a gradient-based fast affine motionestimation algorithm and affine model merge, where the latter attempts to reusethe affine motion parameters (instead of the motion vectors) of neighboringblocks. Third, we propose two fast affine motion compensation algorithms. Oneis the one-step sub-pixel interpolation, which reduces the computations of eachinterpolation. The other is the interpolation-precision-based adaptive blocksize motion compensation, which performs motion compensation at the block levelrather than the pixel level to reduce the interpolation times. Our proposedtechniques have been implemented based on the state-of-the-art high efficiencyvideo coding standard, and the experimental results show that the proposedtechniques altogether achieve on average 11.1% and 19.3% bits saving for randomaccess and low delay configurations, respectively, on typical video sequencesthat have rich rotation or zooming motions. Meanwhile, the computationalcomplexity increases of both encoder and decoder are within an acceptablerange.

An Efficient Four-Parameter Affine Motion Model for Video Coding